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A New UGV Teleoperation Interface for Improved Awareness of Network Connectivity and Physical Surroundings
KTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.ORCID iD: 0000-0002-6716-1111
KTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.ORCID iD: 0000-0002-0483-8391
KTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
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2017 (English)In: Journal of Human-Robot Interaction, E-ISSN 2163-0364, Vol. 6, no 3, p. 48-70Article in journal (Refereed) Published
Abstract [en]

A reliable wireless connection between the operator and the teleoperated unmanned ground vehicle (UGV) is critical in many urban search and rescue (USAR) missions. Unfortunately, as was seen in, for example, the Fukushima nuclear disaster, the networks available in areas where USAR missions take place are often severely limited in range and coverage. Therefore, during mission execution, the operator needs to keep track of not only the physical parts of the mission, such as navigating through an area or searching for victims, but also the variations in network connectivity across the environment. In this paper, we propose and evaluate a new teleoperation user interface (UI) that includes a way of estimating the direction of arrival (DoA) of the radio signal strength (RSS) and integrating the DoA information in the interface. The evaluation shows that using the interface results in more objects found, and less aborted missions due to connectivity problems, as compared to a standard interface. The proposed interface is an extension to an existing interface centered on the video stream captured by the UGV. But instead of just showing the network signal strength in terms of percent and a set of bars, the additional information of DoA is added in terms of a color bar surrounding the video feed. With this information, the operator knows what movement directions are safe, even when moving in regions close to the connectivity threshold.

Place, publisher, year, edition, pages
Journal of Human-Robot Interaction , 2017. Vol. 6, no 3, p. 48-70
Keywords [en]
teleoperation, UGV, search and rescue, FLC, network connectivity, user interface
National Category
Robotics
Identifiers
URN: urn:nbn:se:kth:diva-223539DOI: 10.5898/JHRI.6.3.ParasuramanISI: 000424170700004OAI: oai:DiVA.org:kth-223539DiVA, id: diva2:1184657
Funder
EU, FP7, Seventh Framework Programme, FP7-ICT-609763 TRADR
Note

QC 20180222

Available from: 2018-02-22 Created: 2018-02-22 Last updated: 2018-04-11Bibliographically approved
In thesis
1. Enhancing geometric maps through environmental interactions
Open this publication in new window or tab >>Enhancing geometric maps through environmental interactions
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The deployment of rescue robots in real operations is becoming increasingly commonthanks to recent advances in AI technologies and high performance hardware. Rescue robots can now operate for extended period of time, cover wider areas andprocess larger amounts of sensory information making them considerably more usefulduring real life threatening situations, including both natural or man-made disasters.

In this thesis we present results of our research which focuses on investigating ways of enhancing visual perception for Unmanned Ground Vehicles (UGVs) through environmental interactions using different sensory systems, such as tactile sensors and wireless receivers.

We argue that a geometric representation of the robot surroundings built upon vision data only, may not suffice in overcoming challenging scenarios, and show that robot interactions with the environment can provide a rich layer of new information that needs to be suitably represented and merged into the cognitive world model. Visual perception for mobile ground vehicles is one of the fundamental problems in rescue robotics. Phenomena such as rain, fog, darkness, dust, smoke and fire heavily influence the performance of visual sensors, and often result in highly noisy data, leading to unreliable or incomplete maps.

We address this problem through a collection of studies and structure the thesis as follow:Firstly, we give an overview of the Search & Rescue (SAR) robotics field, and discuss scenarios, hardware and related scientific questions.Secondly, we focus on the problems of control and communication. Mobile robotsrequire stable communication with the base station to exchange valuable information. Communication loss often presents a significant mission risk and disconnected robotsare either abandoned, or autonomously try to back-trace their way to the base station. We show how non-visual environmental properties (e.g. the WiFi signal distribution) can be efficiently modeled using probabilistic active perception frameworks based on Gaussian Processes, and merged into geometric maps so to facilitate the SAR mission. We then show how to use tactile perception to enhance mapping. Implicit environmental properties such as the terrain deformability, are analyzed through strategic glancesand touches and then mapped into probabilistic models.Lastly, we address the problem of reconstructing objects in the environment. Wepresent a technique for simultaneous 3D reconstruction of static regions and rigidly moving objects in a scene that enables on-the-fly model generation. Although this thesis focuses mostly on rescue UGVs, the concepts presented canbe applied to other mobile platforms that operates under similar circumstances. To make sure that the suggested methods work, we have put efforts into design of user interfaces and the evaluation of those in user studies.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2018. p. 58
Series
TRITA-EECS-AVL ; 2018:26
Keywords
Gaussian Processes Robotics UGV Active perception geometric maps
National Category
Engineering and Technology
Research subject
Computer Science
Identifiers
urn:nbn:se:kth:diva-225957 (URN)978-91-7729-720-8 (ISBN)
Public defence
2018-04-18, F3, Lindstedtsvägen 26, Sing-Sing, floor 2, KTH Campus, Stockholm, 10:00 (English)
Opponent
Supervisors
Funder
EU, FP7, Seventh Framework Programme
Note

QC 20180411

Available from: 2018-04-11 Created: 2018-04-11 Last updated: 2018-04-11Bibliographically approved

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Caccamo, SergioBåberg, Fredrik

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