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  • 1.
    Alhusin Alkhdur, Abdullah
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Toward a Sustainable Human-Robot Collaborative Production Environment2017Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    This PhD study aimed to address the sustainability issues of the robotic systems from the environmental and social aspects. During the research, three approaches were developed: the first one an online programming-free model-driven system that utilises web-based distributed human-robot collaboration architecture to perform distant assembly operations. It uses a robot-mounted camera to capture the silhouettes of the components from different angles. Then the system analyses those silhouettes and constructs the corresponding 3D models.Using the 3D models together with the model of a robotic assembly cell, the system guides a distant human operator to assemble the real components in the actual robotic cell. To satisfy the safety aspect of the human-robot collaboration, a second approach has been developed for effective online collision avoidance in an augmented environment, where virtual three-dimensional (3D) models of robots and real images of human operators from depth cameras are used for monitoring and collision detection. A prototype system is developed and linked to industrial robot controllers for adaptive robot control, without the need of programming by the operators. The result of collision detection reveals four safety strategies: the system can alert an operator, stop a robot, move away the robot, or modify the robot’s trajectory away from an approaching operator. These strategies can be activated based on the operator’s location with respect to the robot. The case study of the research further discusses the possibility of implementing the developed method in realistic applications, for example, collaboration between robots and humans in an assembly line.To tackle the energy aspect of the sustainability for the human-robot production environment, a third approach has been developed which aims to minimise the robot energy consumption during assembly. Given a trajectory and based on the inverse kinematics and dynamics of a robot, a set of attainable configurations for the robot can be determined, perused by calculating the suitable forces and torques on the joints and links of the robot. The energy consumption is then calculated for each configuration and based on the assigned trajectory. The ones with the lowest energy consumption are selected.

  • 2.
    Mohammed, Abdullah
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Schmidt, B.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Gao, L.
    Minimizing energy consumption for robot arm movement2014Conference paper (Refereed)
    Abstract [en]

    Robots are widely used in industry due to their efficiency and high performance. Many of them are operating in the manufacturing stage of the production line where the highest percentage of energy is consumed. Therefore, their energy consumption became a major focus for many robots manufacturers and academic research groups. Nevertheless, the optimization of that consumption is still a challenging task which requires a deep understanding of the robot's kinematic and dynamic behaviors. This paper proposes an approach to develop an optimization module using Matlab® to minimize the energy consumptions of the robot's movement. With the help of Denavit-Hartenberg notation, the approach starts first by solving the inverse kinematics of the robot to find a set of feasible joint configurations required to perform the task, solving the inverse kinematics is usually a challenging step which requires in-depth analyses of the robot. The module then solves the inverse dynamics of the robot to analyze the forces and torques applied on each joint and link in the robot. Furthermore, a calculation for the energy consumption is performed for each configuration. The final step of the process represents the optimization of the calculated configurations by choosing the one with the lowest power consumption and sends the results to the robot controller. Three case studies are used to evaluate the performance of the module. The experimental results demonstrate the developed module as a successful tool for energy efficient robot path planning. Further analyses for the results have been done by comparing them with the ones from commercial simulation software. The case studies show that the optimization of the location for the target path could reduce the energy consumption effectively.

  • 3.
    Mohammed, Abdullah
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Schmidt, Bernard
    University of Skövde.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Active collision avoidance for human–robot collaboration driven by vision sensors2016In: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052, p. 1-11Article in journal (Refereed)
    Abstract [en]

    Establishing safe human–robot collaboration is an essential factor for improving efficiency and flexibility in today’s manufacturing environment. Targeting safety in human–robot collaboration, this paper reports a novel approach for effective online collision avoidance in an augmented environment, where virtual three-dimensional (3D) models of robots and real images of human operators from depth cameras are used for monitoring and collision detection. A prototype system is developed and linked to industrial robot controllers for adaptive robot control, without the need of programming by the operators. The result of collision detection reveals four safety strategies: the system can alert an operator, stop a robot, move away the robot, or modify the robot’s trajectory away from an approaching operator. These strategies can be activated based on the operator’s existence and location with respect to the robot. The case study of the research further discusses the possibility of implementing the developed method in realistic applications, for example, collaboration between robots and humans in an assembly line.

  • 4.
    Mohammed, Abdullah
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Schmidt, Bernard
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Liang, Gao
    Minimising Energy Consumption for Robot Arm Movement2014Conference paper (Refereed)
    Abstract [en]

    Robots are widely used in industry due to their efficiency and high performance. Many of them are operating in the manufacturing stage of the production line where the highest percentage of energy is consumed. Therefore, their energy consumption became a major focus for many robots manufacturers and academic research groups. Nevertheless, the optimisation of that consumption is still a challenging task which requires a deep understanding of the robot’s kinematic and dynamic behaviours. This paper proposes an approach to develop an optimisation module using Matlab® to minimise the energy consumptions of the robot’s movement. With the help of Denavit-Hartenberg notation, the approach starts first by solving the inverse kinematics of the robot to find a set of feasible joint configurations required to perform the task, solving the inverse kinematics is usually a challenging step which requires in-depth analyses of the robot. The module then solves the inverse dynamics of the robot to analyse the forces and torques applied on each joint and link in the robot. Furthermore, a calculation for the energy consumption is performed for each configuration. The final step of the process represents the optimisation of the calculated configurations by choosing the one with the lowest power consumption and sends the results to the robot controller. Three case studies are used to evaluate the performance of the module. The experimental results demonstrate the developed module as a successful tool for energy efficient robot path planning. Further analyses for the results have been done by comparing them with the ones from commercial simulation software. The case studies show that the optimisation of the location for the target path could reduce the energy consumption effectively.

  • 5.
    Mohammed, Abdullah
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Brainwaves driven human-robot collaborative assembly2018In: CIRP annals, ISSN 0007-8506, E-ISSN 1726-0604, Vol. 67, no 1, p. 13-16Article in journal (Refereed)
    Abstract [en]

    This paper introduces an approach to controlling an industrial robot using human brainwaves as a means of communication. The developed approach starts by establishing a set of training sessions where an operator is enquired to think about a set of defined commands for the robot and record the brain activities accordingly. The results of the training sessions are then used on the shop floor to translate the brain activities to a set of robot control commands. An industrial case study is carried out to assist the operator in coordinating a collaborative assembly task of a car engine manifold.

  • 6.
    Mohammed, Abdullah
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Vision-Based Robotic Path Following2013In: International Journal of Mechanisms and Robotic Systems, ISSN 2047-7252, Vol. 1, no 1, p. 95-111Article in journal (Refereed)
    Abstract [en]

    Most robotic manufacturing applications nowadays require tedious and expensive pre–programming of the chosen robot, each time when a new task is introduced. In order to eliminate the tedious robot programming for better productivity, this research proposes an adaptive approach that allows a robot to follow any arbitrary robot path defined by an operator. A so–developed system was designed to monitor and control the path following operation locally or remotely through an established web–based architecture, without the need of extra programming. The objective of the research is achieved by integrating an image processing module with a robotic system. The real benefits of such a system are the ability to control and monitor the stepwise processing stages, as well as to automate the whole operation to a certain level of control defined in advance. In particular, this paper introduces a prototype that can be extended to various industrial applications, such as arc welding, laser cutting and water jet cutting, which require controlling the 2D or 3D path of a robot.

  • 7.
    Mohammed, Abdullah
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Gao, R. X.
    Integrated Image Processing and Path Planning for Robotic Sketching2012In: Proceedings of the 8th CIRP Conference on Intelligent Computation in Manufacturing Engineering, 2012Conference paper (Refereed)
  • 8. Schmidt, B.
    et al.
    Mohammed, Abdullah
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Minimising Energy Consumption for Robot Arm Movement2013Conference paper (Refereed)
  • 9.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Mohammed, Abdullah
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    VISION-ASSISTED AND 3D MODEL-BASED REMOTE ASSEMBLY2012In: Proceedings of International Conference on Innovative Design and Manufacturing, 2012Conference paper (Refereed)
  • 10.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Mohammed, Abdullah
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Onori, Mauro
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Remote robotic assembly guided by 3D models linking to a real robot2014In: CIRP annals, ISSN 0007-8506, E-ISSN 1726-0604, Vol. 63, no 1, p. 1-4Article in journal (Refereed)
    Abstract [en]

    This paper presents a 3D model-driven remote robotic assembly system. It constructs 3D models at runtime to represent unknown geometries at the robot side, where a sequence of images from a calibrated camera in different poses is used. Guided by the 3D models over the Internet, a remote operator can manipulate a real robot instantly for remote assembly operations. Experimental results show that the system is feasible to meet industrial assembly requirements with an acceptable level of modelling quality and relatively short processing time. The system also enables programming-free robotic assembly where the real robot follows the human's assembly operations instantly.

  • 11.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Mohammed, Abdullah
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Xi Vincent
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Schmidt, Bernard
    Univ Skövde, Sch Engn Sci, Skövde, Sweden..
    Energy-efficient robot applications towards sustainable manufacturing2018In: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052, Vol. 31, no 8, p. 692-700Article in journal (Refereed)
    Abstract [en]

    The cloud technology provides sustainable solutions to the modern industrial robotic cells. Within the context, the objective of this research is to minimise the energy consumption of robots during assembly in a cloud environment. Given a robot path and based on the inverse kinematics and dynamics of the robot from the cloud, a set of feasible configurations of the robot can be derived, followed by calculating the desirable forces and torques on the joints and links of the robot. Energy consumption is then calculated for each feasible configuration along the path. The ones with the lowest energy consumption are chosen. Since the energy-efficient robot configurations lead to reduced overall energy consumption, this approach becomes instrumental and can be applied to energy-efficient robotic assembly. This cloud-based energy-efficient approach for robotic applications can largely enhance the current practice as demonstrated by the results of three case studies, leading towards sustainable manufacturing.

  • 12.
    Wang, Xi Vincent
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Mohammed, Abdullah
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Cloud-based Robotic System: Architecture Framework and Deployment Models2015In: Proceedings of International Conference on Advanced Technology & Sciences, 2015, p. 297-306Conference paper (Refereed)
    Abstract [en]

    Nowadays Cloud computing has been extended to the manufacturing paradigm, thus forming the Cloud Manufacturing concept, which provides manufacturing as a service. As a specific type of manufacturing facility, robotics can benefit from extended capabilities from the Manufacturing Cloud, including extended hardware limitation, strengthened computing capability and shared knowledge/information. In this research, a novel Cloud-based Robotic System (CRS) is developed. In the proposed framework, the boundaries between local tasks and cloud services are analyzed and defined. With the help of cloud, current robot cells can be improved in terms of response time, flexibility, adaptiveness, energy consumption and eco-/human-friendliness. The proposed framework is evaluated via two case studies. The benefits, requirements and limitations of the cloud robotic research are analyzed till the end of the paper.

1 - 12 of 12
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  • harvard1
  • ieee
  • modern-language-association-8th-edition
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