Conference Paper

Multiple-goal task realization utilizing redundant degrees of freedom of task and tool attachment optimization

Center for Eng., Univ. of Tokyo, Chiba, Japan
DOI: 10.1109/ICRA.2011.5980546 Conference: Robotics and Automation (ICRA), 2011 IEEE International Conference on
Source: IEEE Xplore

ABSTRACT Minimizing the task completion time of manipulator systems is essential in order to achieve high productivity. In this paper, this problem is dealt with by utilizing the redundant degrees of freedom (DOF) of a given task and the tool attachment optimization. For example, in a vision-based inspection where a camera is held by a manipulator, the extra DOF can be brought about by allowing the camera to be translated along its approach axis or rotated about this axis when capturing images. Furthermore, the manipulator end-effector position and orientation is optimized by designing an additional linkage at the manipulator end-effector which is called a tool attachment. A 7-DOF manipulator system is used in the simulations to verify the proposed approach. Results showed that this approach can minimize the task completion time by about 17% compared to conducting only motion coordination.

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Available from: Jun Ota, Sep 04, 2015
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    ABSTRACT: Today, robotics is an important cornerstone of modern industrial production. Robots are used for numerous reasons including reliability and continuously high quality of work. The main decision factor is the overall efficiency of the robotic system in the production line. One key issue for this is the optimality of the whole set of robotic movements for industrial applications , which typically consist of multiple atomic tasks such as welding seams, drilling holes, etc. Currently, in many industrial scenarios such movements are optimized manually. This is costly and error-prone. Therefore , researchers have been working on algorithms for automatic computation of optimal trajectories for several years. This problem gets even more complicated due to multiple additional factors like redundant kinematics, collision avoidance, possibilities of ambiguous task performance, etc. This survey article summarizes and categorizes the approaches for optimization of the robotic task sequence. It provides an overview of existing combinatorial problems that are applied for robot task sequencing. It also highlights the strengths and the weaknesses of existing approaches as well as the challenges for future research in this domain. The article is meant for both scientists and practitioners. For scientists , it provides an overview on applied algorithmic approaches. For practitioners, it presents existing solutions , which are categorized according to the classes of input and output parameters.
    Journal of Intelligent and Robotic Systems 03/2015; DOI:10.1007/s10846-015-0190-6 · 0.81 Impact Factor