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  • 1.
    Aviles, Marcos
    et al.
    GMV, Spain.
    Siozios, Kostas
    School of ECE, National Technical University of Athens, Greece.
    Diamantopoulos, Dionysios
    School of ECE, National Technical University of Athens, Greece.
    Nalpantidis, Lazaros
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Kostavelis, Ioannis
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Boukas, Evangelos
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Soudris, Dimitrios
    School of ECE, National Technical University of Athens, Greece.
    Gasteratos, Antonios
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    A co-design methodology for implementing computer vision algorithms for rover navigation onto reconfigurable hardware2011Inngår i: Proceedings of the FPL2011 Workshop on Computer Vision on Low-Power Reconfigurable Architectures, 2011, s. 9-10Konferansepaper (Annet vitenskapelig)
    Abstract [en]

    Vision-based robotics applications have been widely studied in the last years. However, up to now solutions that have been proposed were affecting mostly software level. The SPARTAN project focuses in the tight and optimal implementation of computer vision algorithms targeting to rover navigation. For evaluation purposes, these algorithms will be implemented with a co-design methodology onto a Virtex-6 FPGA device.

  • 2. Baudoin, Y.
    et al.
    Doroftei, D.
    De Cubber, G.
    Berrabah, S. A.
    Pinzon, C.
    Warlet, F.
    Gancet, J.
    Motard, E.
    Ilzkovitz, M.
    Nalpantidis, Lazaros
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Gasteratos, Antonios
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    View-finder: Robotics assistance to fire-fighting services and crisis management2009Inngår i: Safety, Security & Rescue Robotics (SSRR), 2009 IEEE International Workshop on, 2009, s. 1-6Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In the event of an emergency due to a fire or other crisis, a necessary but time consuming pre-requisite, that could delay the real rescue operation, is to establish whether the ground or area can be entered safely by human emergency workers. The objective of the VIEW-FINDER project is to develop robots which have the primary task of gathering data. The robots are equipped with sensors that detect the presence of chemicals and, in parallel, image data is collected and forwarded to an advanced Control station (COC). The robots will be equipped with a wide array of chemical sensors, on-board cameras, Laser and other sensors to enhance scene understanding and reconstruction. At the Base Station (BS) the data is processed and combined with geographical information originating from a web of sources; thus providing the personnel leading the operation with in-situ processed data that can improve decision making. This paper will focus on the Crisis Management Information System that has been developed for improving a Disaster Management Action Plan and for linking the Control Station with a out-site Crisis Management Centre, and on the software tools implemented on the mobile robot gathering data in the outdoor area of the crisis.

  • 3. Chrysostomou, Dimitrios
    et al.
    Gasteratos, Antonios
    Nalpantidis, Lazaros
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Sirakoulis, Georgios C.
    Multi-view 3D scene reconstruction using ant colony optimization techniques2012Inngår i: Measurement science and technology, ISSN 0957-0233, E-ISSN 1361-6501, Vol. 23, nr 11, s. 114002-Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This paper presents a new method performing high-quality 3D object reconstruction of complex shapes derived from multiple, calibrated photographs of the same scene. The novelty of this research is found in two basic elements, namely: (i) a novel voxel dissimilarity measure, which accommodates the elimination of the lighting variations of the models and (ii) the use of an ant colony approach for further refinement of the final 3D models. The proposed reconstruction procedure employs a volumetric method based on a novel projection test for the production of a visual hull. While the presented algorithm shares certain aspects with the space carving algorithm, it is, nevertheless, first enhanced with the lightness compensating image comparison method, and then refined using ant colony optimization. The algorithm is fast, computationally simple and results in accurate representations of the input scenes. In addition, compared to previous publications, the particular nature of the proposed algorithm allows accurate 3D volumetric measurements under demanding lighting environmental conditions, due to the fact that it can cope with uneven light scenes, resulting from the characteristics of the voxel dissimilarity measure applied. Besides, the intelligent behavior of the ant colony framework provides the opportunity to formulate the process as a combinatorial optimization problem, which can then be solved by means of a colony of cooperating artificial ants, resulting in very promising results. The method is validated with several real datasets, along with qualitative comparisons with other state-of-the-art 3D reconstruction techniques, following the Middlebury benchmark.

  • 4.
    Chrysostomou, Dimitrios
    et al.
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Nalpantidis, Lazaros
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Gasteratos, Antonios
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Lighting compensating multiview stereo2011Inngår i: 2011 IEEE International Conference on Imaging Systems and Techniques, IST 2011 - Proceedings, 2011, s. 176-179Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In this paper, a method that performs 3D object reconstruction from multiple views of the same scene is presented. This reconstruction method initially produces a basic model, based on the space carving algorithm, that is further refined in a subsequent step. The algorithm is fast, computationally simple and produces accurate representations of the input scenes. In addition, compared to previously presented works the proposed algorithm is able to cope with non uniformly lighted scenes due to the characteristics of the used voxel dissimilarity measure. The proposed algorithm is assessed and the experimental results are presented and discussed.

  • 5.
    De Cubber, Geert
    et al.
    Royal Military Academy, Belgium.
    Doroftei, Daniela
    Royal Military Academy, Belgium.
    Nalpantidis, Lazaros
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Sirakoulis, Georgios Ch.
    Electrical and Computer Engineering Dept., Democritus University of Thrace, Greece.
    Gasteratos, Antonios
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Stereo-based terrain traversability analysis for robot navigation2009Inngår i: IARP/EURON Workshop on Robotics for Risky Interventions and Environmental Surveillance, 2009Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Outdoor mobile robots, which have to navigate autonomously in a totally nstructured environment need to auto-determine the suitability of the terrain around them for traversal. Traversability estimation is a challenging problem, as the traversability is a complex function of both the terrain characteristics, such as slopes, vegetation, rocks, etc and the robot mobility characteristics, i.e. locomotion method, wheel properties, etc. In this paper, we present an approach where a classification of the terrain in the classes “traversable” and “obstacle” is performed using only stereo vision as input data. In a first step, high-quality stereo disparity maps are calculated by a fast and robust algorithm. This stereo algorithm is explained in section 3 of this paper. Using this stereo depth information, the terrain classification is performed, based upon the analysis of the so-called "v-disparity" image which provides a representation of the geometric content of the scene. Using this method, it is possible to detect non-traversable terrain items (obstacles) even in the case of partial occlusion and without any explicit extraction of coherent structures or any a priori knowledge of the environment. The sole algorithm parameter is a single factor which takes into account the robot mobility characteristics. This terrain traversability estimation algorithm is explained in section 4. The stereo disparity mapping and terrain traversability estimation processes are integrated in an autonomous robot control architecture, proving that the algorithms allow real-time robot control. The results of experiments with this robot navigating on rough outdoor terrain are presented in section 5.

  • 6.
    De Cubber, Geert
    et al.
    Royal Military Academy, Belgium.
    Nalpantidis, Lazaros
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Sirakoulis, Georgios Ch.
    Electrical and Computer Engineering Dept., Democritus University of Thrace, Greece.
    Gasteratos, Antonios
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Intelligent robots need intelligent vision: Visual 3D perception2008Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Contemporary autonomous robots are generally equipped with an abundance of sensors like for example GPS, Laser, ultrasound sensors, etc to be able to navigate in an environment. However, this stands in contrast to the ultimate biological example for these robots: us humans. Indeed, humans seem perfectly capable to navigate in a complex, dynamic environment using primarily vision as a sensing modality. This observation inspired us to investigate visually guided intelligent mobile robots. In order to understand and reason about its environment, an intelligent robot needs to be aware of the three-dimensional status of this environment. The problem with vision, though, is that the perceived image is a two-dimensional projection of the 3D world. Recovering 3D-information has been in the focus of attention of the computer vision community for a few decades now, yet no all-satisfying method has been found so far. Most attention in this area has been on stereo-vision based methods, which use the displacement of objects in two (or more) images. Where stereo vision must be seen as a spatial integration of multiple viewpoints to recover depth, it is also possible to perform a temporal integration. The problem arising in this situation is known as the "Structure from Motion" (SfM) problem and deals with extracting 3-dimensional information about the environment from the motion of its projection onto a two-dimensional surface. In this paper, we investigate the possibilities of stereo and structure from motion approaches. It is not the aim to compare both theories of depth reconstruction with the goal of designating a winner and a loser. Both methods are capable of providing sparse as well as dense 3D reconstructions and both approaches have their merits and defects. The thorough, year-long research in the field indicates that accurate depth perception requires a combination of methods rather than a sole one. In fact, cognitive research has shown that the human brain uses no less than 12 different cues to estimate depth. Therefore, we also finally introduce in a following section a methodology to integrate stereo and structure from motion.

  • 7.
    Fikos, George
    et al.
    Physics Dept., Aristotle University of Thessaloniki, Greece.
    Nalpantidis, Lazaros
    Physics Dept., Aristotle University of Thessaloniki, Greece.
    Siskos, Stylianos
    Physics Dept., Aristotle University of Thessaloniki, Greece.
    A 32x32 smart photo-array with minimum-size FGMOS for amplification and FPN reduction2005Inngår i: SiPS 2005: IEEE Workshop on Signal Processing Systems - Design and Implementation, 2005, Vol. 2005, s. 199-203Konferansepaper (Fagfellevurdert)
    Abstract [en]

    A logarithmic response photoarray, incorporating two minimum-sized floating-gate mosfets (FGMOS) in its basic photocell, is presented. Exploiting the same FGMOS as an analog memory element for Fixed Pattern Noise (FPN) reduction, and as an inherent amplifying element, is, to our knowledge, novel. The above features, favored by the use of small control gate capacitors, lead to area reduction. The circuit behavior is analyzed and experimental results of a 32×32 prototype array implemented in AMS 0.6Όm CMOS technology, are presented and discussed.

  • 8.
    Fikos, George
    et al.
    Physics Dept., Aristotle University of Thessaloniki, Greece.
    Nalpantidis, Lazaros
    Physics Dept., Aristotle University of Thessaloniki, Greece.
    Siskos, Stylianos
    Physics Dept., Aristotle University of Thessaloniki, Greece.
    A compact APS with FPN reduction and focusing criterion using FGMOS photocell2008Inngår i: Sensors and Actuators A-Physical, ISSN 0924-4247, E-ISSN 1873-3069, Vol. 147, nr 2, s. 419-424Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Prior implementations of CMOS photoarrays with floating-gate MOS (FGMOS), substituted one MOS with a FGMOS in, otherwise, well-established photocell structures. Bipolar manipulation of the floating-gate's charge requires special structures to achieve fixed pattern noise (FPN) suppression. The control capacitor accompanying the FGMOS, needed to be quite larger than the MOS parasitic capacitances, resulting in increased area. Also, output amplification was dealt separately, by additional amplification cells. The proposed logarithmic CMOS photoarray, carefully incorporates two FGMOS in each photocell, favoring the use of minimum control-gate capacitance, achieving area reduction. Unipolar manipulation of floating-gate charge is achieved without special circuitry, preserving FPN suppression. Simultaneously, output amplification is achieved by exploiting the same FGMOS's inherent processing capabilities. A very simple circuit providing a focusing function was also incorporated and successfully tested. Additionally, global normalization towards the average photocurrent, make the circuit ideal preprocessor for image recognition tasks. Experimental results from a 32 × 32 array in AMS 0.6 Όm CMOS technology support the theoretical analysis. © 2008 Elsevier B.V. All rights reserved.

  • 9.
    Fikos, George
    et al.
    Physics Dept., Aristotle University of Thessaloniki, Greece.
    Nalpantidis, Lazaros
    Physics Dept., Aristotle University of Thessaloniki, Greece.
    Siskos, Stylianos
    Physics Dept., Aristotle University of Thessaloniki, Greece.
    A low-voltage, analog power-law function generator2006Inngår i: 2006 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS, VOLS 1-11, PROCEEDINGS, NEW YORK: IEEE , 2006, s. 3818-3821Konferansepaper (Fagfellevurdert)
    Abstract [en]

    A simple low voltage circuit topology able to generate any positive real number power-law function is presented. The proposed circuit exploits BJTs and is based on piecewise linear approximation of the nonlinear function to be generated. An in-depth mathematical analysis is deployed. The instances of a squarer, a cube-law, a square rooting and cube rooting circuit are thoroughly examined through simulation. The obtained results verify the theoretical calculations.

  • 10.
    Hatzopoulos, Alkis A.
    et al.
    Electrical and Computer Engineering Dept., Aristotle University of Thessaloniki, Greece.
    Siskos, Stylianos
    Physics Dept., Aristotle University of Thessaloniki, Greece.
    Dimitriadis, Charalabos A.
    Physics Dept., Aristotle University of Thessaloniki, Greece.
    Papadopoulos, Nikolaos
    Pappas, Ilias
    Physics Dept., Aristotle University of Thessaloniki, Greece.
    Nalpantidis, Lazaros
    Physics Dept., Aristotle University of Thessaloniki, Greece.
    A built-in current sensor using thin-film transistors2005Inngår i: Second Conference on Microelectronics, Microsystems and Nanotechnology, Institute of Physics Publishing (IOPP), 2005, Vol. 10, nr 1, s. 289-292Konferansepaper (Fagfellevurdert)
    Abstract [en]

    A simple current mirror using TFTs with input terminals which are capacitively coupled to the TFT gate, is used in this work, to design a built-in current sensor (BICS). The important feature in this application is that the voltage drop across the sensing TFT device can be reduced to almost zero value, while preserving transistor operation in the saturation region. This makes the proposed BICS appropriate for TFT applications without affecting the circuit operation. It also results in adequate linearity for the current monitoring, making the structure applicable to digital as well as to analog and mixed-signal circuit testing.

  • 11. Kostavelis, I.
    et al.
    Boukas, E.
    Nalpantidis, Lazaros
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Gasteratos, A.
    Path tracing on polar depth maps for robot navigation2012Inngår i: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer Berlin/Heidelberg, 2012, s. 395-404Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In this paper a Cellular Automata-based (CA) path estimation algorithm suitable for safe robot navigation is presented. The proposed method combines well established 3D vision techniques with CA operations and traces a collision free route from the foot of the robot to the horizon of a scene. Firstly, the depth map of the scene is obtained and, then, a polar transformation is applied. A v-disparity image calculation processing step is applied to the initial depth map separating the ground plane from the obstacles. In the next step, a CA floor field is formed representing all the distances from the robot to the traversable regions in the scene. The target point that the robot should move towards to, is tracked down and an additional CA routine is applied to the floor field revealing a traversable route that the robot should follow to reach its target location.

  • 12. Kostavelis, I.
    et al.
    Nalpantidis, Lazaros
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Gasteratos, A.
    Collision risk assessment for autonomous robots by offline traversability learning2012Inngår i: Robotics and Autonomous Systems, ISSN 0921-8890, E-ISSN 1872-793X, Vol. 60, nr 11, s. 1367-1376Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Autonomous robots should be able to move freely in unknown environments and avoid impacts with obstacles. The overall traversability estimation of the terrain and the subsequent selection of an obstacle-free route are prerequisites of a successful autonomous operation. This work proposes a computationally efficient technique for the traversability estimation of the terrain, based on a machine learning classification method. Additionally, a new method for collision risk assessment is introduced. The proposed system uses stereo vision as a first step in order to obtain information about the depth of the scene. Then, a v-disparity image calculation processing step extracts information-rich features about the characteristics of the scene, which are used to train a support vector machine (SVM) separating the traversable and non-traversable scenes. The ones classified as traversable are further processed exploiting the polar transformation of the depth map. The result is a distribution of obstacle existence likelihoods for each direction, parametrized by the robot's embodiment.

  • 13. Kostavelis, I.
    et al.
    Nalpantidis, Lazaros
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Gasteratos, A.
    Object recognition using saliency maps and HTM learning2012Inngår i: Imaging Systems and Techniques (IST), 2012 IEEE International Conference on, IEEE , 2012, s. 528-532Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In this paper a pattern classification and object recognition approach based on bio-inspired techniques is presented. It exploits the Hierarchical Temporal Memory (HTM) topology, which imitates human neocortex for recognition and categorization tasks. The HTM comprises a hierarchical tree structure that exploits enhanced spatiotemporal modules to memorize objects appearing in various orientations. In accordance with HTM's biological inspiration, human vision mechanisms can be used to preprocess the input images. Therefore, the input images undergo a saliency computation step, revealing the plausible information of the scene, where a human might fixate. The adoption of the saliency detection module releases the HTM network from memorizing redundant information and augments the classification accuracy. The efficiency of the proposed framework has been experimentally evaluated in the ETH-80 dataset, and the classification accuracy has been found to be greater than other HTM systems.

  • 14.
    Kostavelis, Ioannis
    et al.
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Boukas, Evangelos
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Nalpantidis, Lazaros
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Gasteratos, Antonios
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Aviles, Marcos
    SPARTAN system: Towards a low-cost and high-performance vision architecture for space exploratory rovers2011Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The “SPAring Robotics Technologies for Autonomous Navigation” (SPARTAN) activity of the European Space Agency (ESA) aims to develop an efficient, low-cost and accurate vision system for the future Martian exploratory rovers. The interest on vision systems for space robots has been steadily growing during the last years. The SPARTAN system considers an optimal implementation of computer vision algorithms for space rover navigation and is desig- nated for application to a space exploratory robotic rover, such as the ExoMars. The goal of the present work is the development of an appropriate architecture for the vision system. Thus, the arrangement and characteristics of the rover’s vision sensors will be defined and the required com- puter vision modules will be presented. The analysis will be performed taking into consideration the constraints defined by ESA about the SPARTAN system.

  • 15.
    Kostavelis, Ioannis
    et al.
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Nalpantidis, Lazaros
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Gasteratos, Antonios
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Comparative presentation of real-time obstacle avoidance algorithms using solely stereo vision2010Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This work presents a comparison between vision-based obstacle avoidance algorithms for mobile robot navigation. The issue of obstacle avoidance in robotics demands a reliable solution since mobile platforms often have to maneuver in arbitrary environments with high level of risk. The most significant advantage of the presented work is the use of only one sensor, i.e. a stereo camera, which significantly diminishes the computational cost. Three different versions of the proposed method have been developed. The implementation of these algorithms consists of a stereo vision module, which is common for all the versions, and a decision making module, which is different in each version and proposes an efficient method of processing stereo information in order to navigate a robotic platform. The algorithms have been implemented in C++ and the produced frame rate ensures that the robot will be able to accomplish the proposed decisions in real time. The presented algorithms have been tested on various different input images and their results are shown and discussed.

  • 16.
    Kostavelis, Ioannis
    et al.
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Nalpantidis, Lazaros
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Gasteratos, Antonios
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Real-time algorithm for obstacle avoidance2009Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This work presents a vision-based obstacle detection and avoidance method for autonomous mobile robots. The implementation of an algorithm able to navigate a robot in arbitrary environments usually demands of the synergy of several sensors. This work presents an algorithm employing only one sensor, i.e. a stereo camera, thus significantly diminishing the system’s complexity. The implementation of this algorithm can be divided into two separate and independent modules. First, the stereo vision module retrieves information from the environment and produces disparity maps and then the decision making module analyses the data of the disparity maps and governs the robot’s direction. The achieved frame rate ensures that the robot will have enough time to accomplish the proposed decisions in real time. Both of the modules have been implemented in C++. The complete algorithm has been examined by being applied on an extensive set of pre-captured stereo images.

  • 17.
    Kostavelis, Ioannis
    et al.
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Nalpantidis, Lazaros
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Gasteratos, Antonios
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Supervised traversability learning for robot navigation2011Inngår i: 12th Annual Conference on Towards Autonomous Robotic Systems, TAROS 2011, Springer Berlin/Heidelberg, 2011, Vol. 6856 LNAI, s. 289-298Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This work presents a machine learning method for terrain's traversability classification. Stereo vision is used to provide the depth map of the scene. Then, a v-disparity image calculation and processing step extracts suitable features about the scene's characteristics. The resulting data are used as input for the training of a support vector machine (SVM). The evaluation of the traversability classification is performed with a leave-one-out cross validation procedure applied on a test image data set. This data set includes manually labeled traversable and non-traversable scenes. The proposed method is able to classify the scene of further stereo image pairs as traversable or non-traversable, which is often the first step towards more advanced autonomous robot navigation behaviours.

  • 18.
    Nalpantidis, Lazaros
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Study and implementation of stereo vision systems for robotic applications2010Doktoravhandling, monografi (Annet vitenskapelig)
    Abstract [en]

    Stereo vision has been chosen by natural selection as the most common way to estimate the depth of objects. A pair of two-dimensional images is enough in order to retrieve the third dimension of the scene under observation. The importance of this method is great, apart from the living creatures, for sophisticated machine systems, as well. During the last years robotics has made significant progress and the state of the art is now about achieving autonomous behaviors. In order to accomplish the target of robots being able to move and act autonomously, accurate representations of their environments are required. Both these fields, stereo vision and accomplishing autonomous robotic behaviors, have been in the center of this PhD thesis. The issue of robots using machine stereo vision is not a new one. The number and significance of the researchers that have been involved, as well as the publishing rate of relevant scientific papers indicates an issue that is interesting and still open to solutions and fresh ideas rather than a banal and solved issue. The motivation of this PhD thesis has been the observation that the combination of stereo vision usage and autonomous robots is usually performed in a simplistic manner of simultaneously using two independent technologies. This situation is owed to the fact that the two technologies have evolved independently and by different scientific communities. Stereo vision has mainly evolved within the field of computer vision. On the other hand, autonomous robots are a branch of the robotics and mechatronics field. Methods that have been proposed within the frame of computer vision are not generally satisfactory for use in robotic applications. This fact is due to that an autonomous robot places strict constraints concerning the demanded speed of calculations and the available computational resources. Moreover, their inefficiency is commonly owed to factors related to the environments and the conditions of operation. As a result, the used algorithms, in this case the stereo vision algorithms, should take into consideration these factors during their development. The required compromises have to retain the functionality of the integrated system. The objective of this PhD thesis is the development of stereo vision systems customized for use in autonomous robots. Initially, a literature survey was conducted concerning stereo vision algorithms and corresponding robotic applications. The survey revealed the state of the art in the specific field and pointed out issues that had not yet been answered in a satisfactory manner. Afterwards, novel stereo vision algorithms were developed, which satisfy the demands posed by robotic systems and propose solutions to the open issues indicated by the literature survey. Finally, systems that embody the proposed algorithms and treat open robotic applications’ issues have been developed. Within this dissertation there have been used for the first time and combined in a novel way various computational tools and ideas originating from different scientific fields. There have been used biologically and psychologically inspired methods, such as the logarithmic response law (Weber-Fechner law) and the gestalt laws of perceptual organization (proximity, similarity and continuity). Furthermore, there have been used sophisticated computational methods, such as 2D and 3D cellular automata and fuzzy inference systems for computer vision applications. Additionally, ideas from the field of video coding have been incorporated in stereo vision applications. The resulting methods have been applied to basic computer vision depth extraction applications and even to advanced autonomous robotic behaviors. In more detail, the possibility of implementing effective hardware-implementable stereo correspondence algorithms has been investigated. Specifically, an algorithm that combines rapid execution, simple and straight-forward structure, as well as high-quality of results is presented. These features render it as an ideal candidate for hardware implementation and for real-time applications. The algorithm utilizes Gaussian aggregation weights and 3D cellular automata in order to achieve high-quality results. This algorithm comprised the basis of a multi-view stereo vision system. The final depth map is produced as a result of a certainty assessment procedure. Moreover, a new hierarchical correspondence algorithm is presented, inspired by motion estimation techniques originally used in video encoding. The algorithm performs a 2D correspondence search using a similar hierarchical search pattern and the intermediate results are refined by 3D cellular automata. This algorithm can process uncalibrated and non-rectified stereo image pairs, maintaining the computational load within reasonable levels. It is well known that non-ideal environmental conditions, such as differentiations in illumination depending on the viewpoint heavily affect the stereo algorithms’ performance. In this PhD thesis a new illumination-invariant pixels’ dissimilarity measure is presented that can substitute the established intensity-based ones. The proposed measure can be adopted by almost any of the existing stereo algorithms, enhancing them with its robust features. The algorithm using the proposed dissimilarity measure has outperformed all the other examined algorithms, exhibiting tolerance to illumination differentiations and robust behavior. Moreover, a novel stereo correspondence algorithm that incorporates many biologically and psychologically in- spired features to an adaptive weighted sum of absolute differences framework is presented. In addition to ideas already exploited, such as the color information utilization, gestalt laws of proximity and similarity, new ones have been adopted. The algorithm introduces the use of circular support regions, the gestalt law of continuity, as well as the psychophysically-based logarithmic response law. All the aforementioned perceptual tools act complementarily inside a straight-forward computational algorithm. Furthermore, stereo correspondence algorithms have been further exploited as the basis of more advanced robotic behaviors. Vision-based obstacle avoidance algorithms for autonomous mobile robots are presented. These algorithms avoid, as much as possible, computationally complex processes. The only sensor required is a stereo camera. The algorithms consist of two building blocks. The first one is a stereo algorithm, able to provide reliable depth maps of the scenery in frame rates suitable for a robot to move autonomously. The second building block is either a simple decision- making algorithm or a fuzzy logic-based one, which analyze the depth maps and deduce the most appropriate direction for the robot to avoid any existing obstacles. Finally, a visual Simultaneous Localization and Mapping (SLAM) algorithm suitable for indoor applications is proposed. The algorithm is focused on computational effectiveness and the only sensor used is a stereo camera placed onboard a moving robot. The algorithm processes the acquired images calculating the depth of the scenery, detecting occupied areas and progressively building a map of the environment. The stereo vision-based SLAM algorithm embodies a custom-tailored stereo correspondence algorithm, the robust scale and rotation invariant feature detection and matching "Speeded Up Robust Features" (SURF) method, a computationally effective v-disparity image calculation scheme, a novel map-merging module, as well as a sophisticated cellular automata-based enhancement stage.

  • 19.
    Nalpantidis, Lazaros
    et al.
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Amanatiadis, Angelos
    Electrical and Computer Engineering Dept., Democritus University of Thrace, Greece.
    Sirakoulis, Georgios Ch.
    Electrical and Computer Engineering Dept., Democritus University of Thrace, Greece.
    Gasteratos, Antonios
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Efficient hierarchical matching algorithm for processing uncalibrated stereo vision images and its hardware architecture2011Inngår i: IET Image Processing, ISSN 1751-9659, E-ISSN 1751-9667, Vol. 5, nr 5, s. 481-492Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In motion estimation, the sub-pixel matching technique involves the search of sub-sample positions as well as integer-sample positions between the image pairs, choosing the one that gives the best match. Based on this idea, this work proposes an estimation algorithm, which performs a 2-D correspondence search using a hierarchical search pattern. The intermediate results are refined by 3-D cellular automata (CA). The disparity value is then defined using the distance of the matching position. Therefore the proposed algorithm can process uncalibrated and non-rectified stereo image pairs, maintaining the computational load within reasonable levels. Additionally, a hardware architecture of the algorithm is deployed. Its performance has been evaluated on both synthetic and real self-captured image sets. Its attributes, make the proposed method suitable for autonomous outdoor robotic applications.

  • 20.
    Nalpantidis, Lazaros
    et al.
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Amanatiadis, Angelos
    Electrical and Computer Engineering Dept., Democritus University of Thrace, Greece.
    Sirakoulis, Georgios Ch.
    Electrical and Computer Engineering Dept., Democritus University of Thrace, Greece.
    Kyriakoulis, Nikolaos
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Gasteratos, Antonios
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Dense disparity estimation using a hierarchical matching technique from uncalibrated stereo vision2009Inngår i: IST: 2009 IEEE INTERNATIONAL WORKSHOP ON IMAGING SYSTEMS AND TECHNIQUES, NEW YORK: IEEE , 2009, s. 422-426Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In motion estimation, the sub-pixel matching technique involves the search of sub-sample positions as well as integer-sample positions between the image pairs, choosing the one that gives the best match. Based on this idea, the proposed disparity estimation algorithm performs a 2-D correspondence search using a hierarchical search pattern. The disparity value is then defined using the distance of the matching position. Therefore, the proposed algorithm can process non-rectified stereo image pairs, maintaining the computational load within reasonable levels.

  • 21.
    Nalpantidis, Lazaros
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Björkman, Mårten
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    YES - YEt another object Segmentation: exploiting camera movement2012Inngår i: Intelligent Robots and Systems (IROS), 2012 IEEE/RSJ International Conference on, IEEE , 2012, s. 2116-2121Konferansepaper (Fagfellevurdert)
    Abstract [en]

    We address the problem of object segmentation in image sequences where no a-priori knowledge of objects is assumed. We take advantage of robots' ability to move, gathering multiple images of the scene. Our approach starts by extracting edges, uses a polar domain representation and performs integration over time based on a simple dilation operation. The proposed system can be used for providing reliable initial segmentation of unknown objects in scenes of varying complexity, allowing for recognition, categorization or physical interaction with the objects. The experimental evaluation on both self-captured and a publicly available dataset shows the efficiency and stability of the proposed method.

  • 22.
    Nalpantidis, Lazaros
    et al.
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Chrysostomou, Dimitrios
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Gasteratos, Antonios
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Obtaining reliable depth maps for robotic applications from a quad-camera system2009Inngår i: INTELLIGENT ROBOTICS AND APPLICATIONS, PROCEEDINGS, Berlin: Springer Berlin/Heidelberg, 2009, Vol. 5928 LNAI, s. 906-916Konferansepaper (Annet vitenskapelig)
    Abstract [en]

    Autonomous navigation behaviors in robotics often require reliable depth maps. The use of vision sensors is the most popular choice in such tasks. On the other hand, accurate vision-based depth computing methods suffer from long execution times. This paper proposes a novel quad-camera based system able to calculate fast and accurately a single depth map of a scenery. The four cameras are placed on the corners of a square. Thus, three, differently oriented, stereo pairs result when considering a single reference image (namely an horizontal, a vertical and a diagonal pair). The proposed system utilizes a custom tailored, simple, rapidly executed stereo correspondence algorithm applied to each stereo pair. This way, the computational load is kept within reasonable limits. A reliability measure is used in order to validate each point of the resulting disparity maps. Finally, the three disparity maps are fused together according to their reliabilities. The maximum reliability is chosen for every pixel. The final output of the proposed system is a highly reliable depth map which can be used for higher level robotic behaviors.

  • 23.
    Nalpantidis, Lazaros
    et al.
    Physics Dept., Aristotle University of Thessaloniki, Greece.
    Fikos, George
    Physics Dept., Aristotle University of Thessaloniki, Greece.
    Siskos, Stylianos
    Physics Dept., Aristotle University of Thessaloniki, Greece.
    A low-voltage, low-power generalized power-law function generator2005Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In this paper a simple low voltage circuit topology able to generate any positive integer power-law function is presented. The proposed circuit exploits MOSFETs operating in the weak inversion regime and is based on piecewise linear approximation of the nonlinear function to be generated. An in-depth mathematical analysis is deployed. The instances of a squarer and a cube-law circuit are thoroughly examined through simulation and the results are presented.

  • 24.
    Nalpantidis, Lazaros
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Gasteratos, A.
    Stereo vision depth estimation methods for robotic applications2013Inngår i: Robotics: Concepts, Methodologies, Tools, and Applications, IGI Global, 2013, Vol. 3, s. 1461-1481Kapittel i bok, del av antologi (Annet vitenskapelig)
    Abstract [en]

    Vision is undoubtedly the most important sense for humans. Apart from many other low and higher level perception tasks, stereo vision has been proven to provide remarkable results when it comes to depth estimation. As a result, stereo vision is a rather popular and prosperous subject among the computer and machine vision research community. Moreover, the evolution of robotics and the demand for visionbased autonomous behaviors has posed new challenges that need to be tackled. Autonomous operation of robots in real working environments, given limited resources requires effective stereo vision algorithms. This chapter presents suitable depth estimation methods based on stereo vision and discusses potential robotic applications.

  • 25.
    Nalpantidis, Lazaros
    et al.
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Gasteratos, Antonios
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Biologically and psychophysically inspired adaptive support weights algorithm for stereo correspondence2010Inngår i: Robotics and Autonomous Systems, ISSN 0921-8890, E-ISSN 1872-793X, Vol. 58, nr 5, s. 457-464Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In this paper a novel stereo correspondence algorithm is presented. It incorporates many biologically and psychologically inspired features to an adaptive weighted sum of absolute differences (SAD) framework in order to determine the correct depth of a scene. In addition to ideas already exploited, such as the color information utilization, gestalt laws of proximity and similarity, new ones have been adopted. The presented algorithm introduces the use of circular support regions, the gestalt law of continuity as well as the psychophysically-based logarithmic response law. All the aforementioned perceptual tools act complementarily inside a straightforward computational algorithm applicable to robotic applications. The results of the algorithm have been evaluated and compared to those of similar algorithms.

  • 26.
    Nalpantidis, Lazaros
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Gasteratos, Antonios
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Stereo vision depth estimation methods for robotic applications2011Inngår i: Depth Map and 3D Imaging Applications: Algorithms and Technologies / [ed] A. S. Malik, T.-S. Choi, and H. Nisar, IGI Global, 2011, s. 397-417Kapittel i bok, del av antologi (Fagfellevurdert)
    Abstract [en]

    Vision is undoubtedly the most important sense for humans. Apart from many other low and higher level perception tasks, stereo vision has been proven to provide remarkable results when it comes to depth estimation. As a result, stereo vision is a rather popular and prosperous subject among the computer and machine vision research community. Moreover, the evolution of robotics and the demand for vision-based autonomous behaviors has posed new challenges that need to be tackled. Autonomous operation of robots in real working environments, given limited resources requires effective stereo vision algorithms. This chapter presents suitable depth estimation methods based on stereo vision and discusses potential robotic applications.

  • 27.
    Nalpantidis, Lazaros
    et al.
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Gasteratos, Antonios
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Stereo vision for robotic applications in the presence of non-ideal lighting conditions2010Inngår i: Image and Vision Computing, ISSN 0262-8856, E-ISSN 1872-8138, Vol. 28, nr 6, s. 940-951Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Many robotic and machine-vision applications rely on the accurate results of stereo correspondence algorithms. However, difficult environmental conditions, such as differentiations in illumination depending on the viewpoint, heavily affect the stereo algorithms' performance. This work proposes a new illumination-invariant dissimilarity measure in order to substitute the established intensity-based ones. The proposed measure can be adopted by almost any of the existing stereo algorithms, enhancing it with its robust features. The performance of the dissimilarity measure is validated through experimentation with a new adaptive support weight (ASW) stereo correspondence algorithm. Experimental results for a variety of lighting conditions are gathered and compared to those of intensity-based algorithms. The algorithm using the proposed dissimilarity measure outperforms all the other examined algorithms, exhibiting tolerance to illumination differentiations and robust behavior.

  • 28.
    Nalpantidis, Lazaros
    et al.
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Gasteratos, Antonios
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Stereovision-based fuzzy obstacle avoidance method2011Inngår i: International Journal of Humanoid Robotics, ISSN 0219-8436, Vol. 8, nr 1, s. 169-183Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This work presents a stereovision-based obstacle avoidance method for autonomous mobile robots. The decision about the direction on each movement step is based on a fuzzy inference system. The proposed method provides an efficient solution that uses a minimum of sensors and avoids computationally complex processes. The only sensor required is a stereo camera. First, a custom stereo algorithm provides reliable depth maps of the environment in frame rates suitable for a robot to move autonomously. Then, a fuzzy decision making algorithm analyzes the depth maps and deduces the most appropriate direction for the robot to avoid any existing obstacles. The proposed methodology has been tested on a variety of self-captured outdoor images and the results are presented and discussed.

  • 29.
    Nalpantidis, Lazaros
    et al.
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Kalomiros, John
    Informatics and Communications Dept., Technological Educational Institute of Serres, Greece.
    Gasteratos, Antonios
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Robust 3D vision for robots using dynamic programming2011Inngår i: 2011 IEEE International Conference on Imaging Systems and Techniques, IST 2011 - Proceedings, VDE Verlag GmbH, 2011, s. 89-93Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In this paper a new stereo vision method is presented that combines the use of a lightness-invariant pixel dissimilarity measure within a dynamic programming depth estimation framework. This method uses concepts such as the proper projection of the HSL colorspace for lightness tolerance, as well as the Gestalt-based adaptive support weight aggregation and a dynamic programming optimization scheme. The robust behavior of this method is suitable for the working environments of outdoor robots, where non ideal lighting conditions often occur. Such problematic conditions heavily affect the efficiency of robot vision algorithms in exploration, military and security applications. The proposed algorithm is presented and applied to standard image sets.

  • 30.
    Nalpantidis, Lazaros
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Kostavelis, I.
    Gasteratos, A.
    Intelligent stereo vision in autonomous robot traversability estimation2012Inngår i: Robotic Vision: Technologies for Machine Learning and Vision Applications, IGI Global, 2012, s. 193-209Kapittel i bok, del av antologi (Fagfellevurdert)
    Abstract [en]

    Traversability estimation is the process of assessing whether a robot is able to move across a specific area. Autonomous robots need to have such an ability to automatically detect and avoid non-traversable areas and, thus, stereo vision is commonly used towards this end constituting a reliable solution under a variety of circumstances. This chapter discusses two different intelligent approaches to assess the traversability of the terrain in front of a stereo vision-equipped robot. First, an approach based on a fuzzy inference system is examined and then another approach is considered, which extracts geometrical descriptions of the scene depth distribution and uses a trained support vector machine (SVM) to assess the traversability. The two methods are presented and discussed in detail.

  • 31.
    Nalpantidis, Lazaros
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Kostavelis, I.
    Gasteratos, A.
    Intelligent stereo vision in autonomous robot traversability estimation2013Inngår i: Robotics: Concepts, Methodologies, Tools, and Applications, IGI Global, 2013, Vol. 1, s. 350-365Kapittel i bok, del av antologi (Annet vitenskapelig)
    Abstract [en]

    Traversability estimation is the process of assessing whether a robot is able to move across a specific area. Autonomous robots need to have such an ability to automatically detect and avoid non-traversable areas and, thus, stereo vision is commonly used towards this end constituting a reliable solution under a variety of circumstances. This chapter discusses two different intelligent approaches to assess the traversability of the terrain in front of a stereo vision-equipped robot. First, an approach based on a fuzzy inference system is examined and then another approach is considered, which extracts geometrical descriptions of the scene depth distribution and uses a trained support vector machine (SVM) to assess the traversability. The two methods are presented and discussed in detail.

  • 32.
    Nalpantidis, Lazaros
    et al.
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Kostavelis, Ioannis
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Gasteratos, Antonios
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Stereovision-based algorithm for obstacle avoidance2009Inngår i: Intelligent Robotics And Applications, Proceedings / [ed] Xie, M; Xiong, Y; Xiong, C; Liu, H; Hu, Z, Springer Berlin/Heidelberg, 2009, Vol. 5928 LNAI, s. 195-204Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This work presents a vision-based obstacle avoidance algorithm for autonomous mobile robots. It provides an efficient solution that uses a minimum of sensors and avoids, as much as possible, computationally complex processes. The only sensor required is a stereo camera. The proposed algorithm consists of two building blocks. The first one is a stereo algorithm, able to provide reliable depth maps of the scenery in frame rates suitable for a robot to move autonomously. The second building block is a decision making algorithm that analyzes the depth maps and deduces the most appropriate direction for the robot to avoid any existing obstacles. The proposed methodology has been tested on sequences of self-captured outdoor images and its results have been evaluated. The performance of the algorithm is presented and discussed.

  • 33.
    Nalpantidis, Lazaros
    et al.
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Sirakoulis, Georgios Ch.
    Electrical and Computer Engineering Dept., Democritus University of Thrace, Greece.
    Carbone, Andrea
    Computer and System Sciences, Sapienza University of Rome, Italy.
    Gasteratos, Antonios
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Computationally effective stereovision SLAM2010Inngår i: 2010 IEEE International Conference on Imaging Systems and Techniques, IST 2010 - Proceedings, IEEE , 2010, s. 458-463Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In this paper a visual Simultaneous Localization and Mapping (SLAM) algorithm suitable for indoor area measurement applications is proposed. The algorithm is focused on computational effectiveness. The only sensor used is a stereo camera placed onboard a moving robot. The algorithm processes the acquired images calculating the depth of the scenery, detecting occupied areas and progressively building a map of the environment. The stereo vision-based SLAM algorithm embodies a custom-tailored stereo correspondence algorithm, the robust scale and rotation invariant feature detection and matching Speeded Up Robust Features (SURF) method, a computationally effective v-disparity image calculation scheme, a novel map-merging module, as well as a sophisticated Cellular Automata (CA)-based enhancement stage. The proposed algorithm is suitable for autonomously mapping and measuring indoor areas using robots. The algorithm is presented and experimental results for self-captured image sets are provided and analyzed.

  • 34.
    Nalpantidis, Lazaros
    et al.
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Sirakoulis, Georgios Ch.
    Electrical and Computer Engineering Dept., Democritus University of Thrace, Greece.
    Gasteratos, Antonios
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    A dense stereo correspondence algorithm for hardware implementation with enhanced disparity selection2008Inngår i: Artificial Intelligence: Theories, Models And Applications, Setn 2008 / [ed] Darzentas, J; Vouros, GA; Arnellos, A, Springer Berlin/Heidelberg, 2008, Vol. 5138 LNAI, s. 365-370Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In this paper an effective, hardware oriented stereo correspondence algorithm, able to produce dense disparity maps of improved fidelity is presented. The proposed algorithm combines rapid execution, simple and straight-forward structure as well as comparably high quality of results. These features render it as an ideal candidate for hardware implementation and for real-time applications. The proposed algorithm utilizes the Absolute Differences (AD) as matching cost and aggregates the results inside support windows, assigning Gaussian distributed weights to the support pixels, based on their Euclidean distance. The resulting Disparity Space Image (DSI) is furthered refined by Cellular Automata (CA) acting in all of the three dimensions of the DSI. The algorithm is applied to typical as well as to self-recorded real-life image sets. The disparity maps obtained are presented and quantitatively examined.

  • 35.
    Nalpantidis, Lazaros
    et al.
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Sirakoulis, Georgios Ch.
    Electrical and Computer Engineering Dept., Democritus University of Thrace, Greece.
    Gasteratos, Antonios
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Non-probabilistic cellular automata-enhanced stereo vision simultaneous localization and mapping2011Inngår i: Measurement science and technology, ISSN 0957-0233, E-ISSN 1361-6501, Vol. 22, nr 11, s. 114027-Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In this paper, a visual non-probabilistic simultaneous localization and mapping (SLAM) algorithm suitable for area measurement applications is proposed. The algorithm uses stereo vision images as its only input and processes them calculating the depth of the scenery, detecting occupied areas and progressively building a map of the environment. The stereo vision-based SLAM algorithm embodies a stereo correspondence algorithm that is tolerant to illumination differentiations, the robust scale- and rotation-invariant feature detection and matching speeded-up robust features method, a computationally effective v-disparity image calculation scheme, a novel map-merging module, as well as a sophisticated cellular automata-based enhancement stage. A moving robot equipped with a stereo camera has been used to gather image sequences and the system has autonomously mapped and measured two different indoor areas.

  • 36.
    Nalpantidis, Lazaros
    et al.
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Sirakoulis, Georgios Ch.
    Electrical and Computer Engineering Dept., Democritus University of Thrace, Greece.
    Gasteratos, Antonios
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Review of stereo matching algorithms for 3D vision2007Inngår i: 16th International Symposium on Measurement and Control in Robotics, 2007Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Stereo vision, resulting in the knowledge of deep information in a scene, is of great importance in the field of machine vision, robotics and image analysis. As a result, in order to address the problem of matching points between two images of a stereo pair several algorithms have been proposed so far. In this paper, an explicit analysis of the existing stereo matching methods, up to date, is presented in full detail. The algorithms found in literature can be grouped into those producing sparse output and those giving a dense result, while the later can be classified as local (area-based) and global (energy- based). The presented algorithms are discussed in terms of speed, accuracy, coverage, time consumption and disparity range. Comparative test results concerning different image sizes as well as different stereo data sets are presented. Furthermore, the usage of advanced computational intelligence techniques such as neural networks and cellular automata in the development and application of such algorithms is also considered. However, due to the fact that the resulting depth calculation is a computationally demanding procedure, most of the presented algorithms perform poorly in real-time applications. Towards this direction, the development of real-time stereo matching algorithms, able to be efficiently implemented in dedicated hardware is of great interest in the contexts of 3D reconstruction, simultaneous localization and mapping (SLAM), virtual reality, robot navigation and control. Some possible implementations of stereo- matching algorithms in hardware for real-time applications are also discussed in details.

  • 37.
    Nalpantidis, Lazaros
    et al.
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Sirakoulis, Georgios Ch.
    Electrical and Computer Engineering Dept., Democritus University of Thrace, Greece.
    Gasteratos, Antonios
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Review of stereo vision algorithms: From software to hardware2008Inngår i: International Journal of Optomechatronics, ISSN 1559-9612, Vol. 2, nr 4, s. 435-462Artikkel, forskningsoversikt (Fagfellevurdert)
    Abstract [en]

    Stereo vision, resulting in the knowledge of deep information in a scene, is of great importance in the field of machine vision, robotics and image analysis. In this article, an explicit analysis of the existing stereo matching methods, up to date, is presented. The presented algorithms are discussed in terms of speed, accuracy, coverage, time consumption, and disparity range. Towards the direction of real-time operation, the development of stereo matching algorithms, suitable for efficient hardware implementation is highly desirable. Implementations of stereo matching algorithms in hardware for real-time applications are also discussed in details.

  • 38.
    Pappas, Ilias
    et al.
    Physics Dept., Aristotle University of Thessaloniki, Greece.
    Nalpantidis, Lazaros
    Physics Dept., Aristotle University of Thessaloniki, Greece.
    Kalenteridis, V.
    Physics Dept., Aristotle University of Thessaloniki, Greece.
    Siskos, Stylianos
    Physics Dept., Aristotle University of Thessaloniki, Greece.
    Dimitriadis, Charalabos A.
    Physics Dept., Aristotle University of Thessaloniki, Greece.
    Hatzopoulos, Alkis A.
    Electrical and Computer Engineering Dept., Aristotle University of Thessaloniki, Greece.
    A study of different types of current mirrors using polysilicon TFTs2005Inngår i: JOURNAL OF PHYSICS CONFERENCE SERIES Vol. 10, Institute of Physics Publishing (IOPP), 2005, Vol. 10, nr 1, s. 373-376Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Polysilicon thin-film technology has become of great interest due to the demand for large area electronic devices. Active Matrix Liquid Crystal Displays (AMLCDs) and Active Matrix Organic Light Emitting Displays (AMOLEDs) are among the fields where polysilicon thin-film transistors (poly-Si TFTs) are most commonly used. Such devices, generally, require analog signal processing. This fact makes the performance of basic analog blocks, such as current mirrors implemented with poly-Si TFTs, crucial. This paper examines the performance of various current mirror designs through simulation. Finally, a novel design of a current mirror is proposed aimed to be used in low voltage applications.

     

  • 39.
    Pappas, Ilias
    et al.
    Physics Dept., Aristotle University of Thessaloniki, Greece.
    Nalpantidis, Lazaros
    Physics Dept., Aristotle University of Thessaloniki, Greece.
    Kalenteridis, Vassilios
    Physics Dept., Aristotle University of Thessaloniki, Greece.
    Siskos, Stylianos
    Physics Dept., Aristotle University of Thessaloniki, Greece.
    Hatzopoulos, Alkis A.
    Electrical and Computer Engineering Dept., Aristotle University of Thessaloniki, Greece.
    Dimitriadis, Charalabos A.
    Physics Dept., Aristotle University of Thessaloniki, Greece.
    A threshold voltage variation cancellation technique for analogue peripheral circuits of a display array using Poly-Si TFTs2006Inngår i: 2006 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS, VOLS 1-11, PROCEEDINGS, 2006, s. 3305-3308Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Polysilicon thin-film technology has become of great interest due to the demand for large area electronic devices. Display applications, memories and optical copier are among the fields where polysilicon thin-film transistors (poly-Si TFTs) are most commonly used. However the design of analogue blocks, by using Poly-Si TFTs, with constant specifications is very difficult because of the large variation of the threshold voltage of the poly-Si TFT across the wafer and the kink effect makes. In this paper we propose a new circuit that can sense the voltage difference between two TFTs. This voltage can be used in order to design an improved current mirror with cancellation of threshold voltage variation.

  • 40.
    Pappas, Ilias
    et al.
    Physics Dept., Aristotle University of Thessaloniki, Greece.
    Nalpantidis, Lazaros
    Physics Dept., Aristotle University of Thessaloniki, Greece.
    Siskos, Stylianos
    Physics Dept., Aristotle University of Thessaloniki, Greece.
    A new analogue driver using poly-Si thin-film transistors for active matrix displays2005Inngår i: XX Conference on Design of Circuits and Integrated Systems, 2005Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Polysilicon thin-film technology has become of great interest due to the demand of large area electronics devices. Active Matrix Liquid Crystal Displays (AMLCD) and Active Matrix Organic Light Emitting Displays are among the fields where the polysilicon thin film transistors (Poly-Si TFTs) are most commonly used. The large variation of the threshold voltage and the mobility of the carriers across the wafer, however, make it difficult to design analogue blocks with constant specifications. Although these problems are related to the fabrication process, circuits have been developed to reduce their impact. In this work an improved AMLCD driver circuit is proposed.

  • 41. Siozios, K.
    et al.
    Diamantopoulos, D.
    Kostavelis, Ioannis
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Boukas, Evangelos
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Nalpantidis, Lazaros
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Soudris, D.
    Gasteratos, Antonios
    Production and Management Engineering Dept., Democritus University of Thrace, Greece.
    Aviles, M.
    Anagnostopoulos, I.
    SPARTAN project: Efficient implementation of computer vision algorithms onto reconfigurable platform targeting to space applications2011Inngår i: 6th International Workshop on Reconfigurable Communication-Centric Systems-on-Chip, ReCoSoC 2011 - Proceedings, 2011Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Vision-based robotic applications exhibit increased computational complexity. This problem becomes even more important regarding mission critical application domains. The SPARTAN project focuses in the tight and optimal implementation of computer vision algorithms targeting to rover navigation for space applications. For evaluation purposes, these algorithms will be implemented with a co-design methodology onto a Virtex-6 FPGA device.

  • 42.
    Smith, Christian
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Karayiannidis, Ioannis
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Nalpantidis, Lazaros
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Gratal, Javier
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Qi, Peng
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Dimarogonas, Dimos
    KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Dual arm manipulation-A survey2012Inngår i: Robotics and Autonomous Systems, ISSN 0921-8890, E-ISSN 1872-793X, Vol. 60, nr 10, s. 1340-1353Artikkel, forskningsoversikt (Fagfellevurdert)
    Abstract [en]

    Recent advances in both anthropomorphic robots and bimanual industrial manipulators had led to an increased interest in the specific problems pertaining to dual arm manipulation. For the future, we foresee robots performing human-like tasks in both domestic and industrial settings. It is therefore natural to study specifics of dual arm manipulation in humans and methods for using the resulting knowledge in robot control. The related scientific problems range from low-level control to high level task planning and execution. This review aims to summarize the current state of the art from the heterogenous range of fields that study the different aspects of these problems specifically in dual arm manipulation.

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