Optimized vision-based robot motion planning from multiple demonstrations

This paper combines workspace models with optimization techniques to simultaneously address whole-arm collision avoidance, joint limits and camera field of view (FOV) limits for vision-based motion planning of a robot manipulator. A small number of user demonstrations are used to generate a feasible...

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Bibliographic Details
Published in:Autonomous robots 2018-08, Vol.42 (6), p.1117-1132
Main Authors: Shen, Tiantian, Radmard, Sina, Chan, Ambrose, Croft, Elizabeth A., Chesi, Graziano
Format: Article
Language:English
Subjects:
Algorithms
Artificial Intelligence
Cameras
Collision avoidance
Computer Imaging
Control
Engineering
Field of view
Grasping (robotics)
Mechatronics
Motion planning
Optimization
Optimization techniques
Pattern Recognition and Graphics
Polynomials
Robot arms
Robot dynamics
Robotics
Robotics and Automation
Robots
Splines
Trajectory control
Vision
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Summary:This paper combines workspace models with optimization techniques to simultaneously address whole-arm collision avoidance, joint limits and camera field of view (FOV) limits for vision-based motion planning of a robot manipulator. A small number of user demonstrations are used to generate a feasible domain over which the whole robot arm can servo without violating joint limits or colliding with obstacles. Our algorithm utilizes these demonstrations to generate new feasible trajectories that keep the target in the camera’s FOV and achieve the desired view of the target (e.g., a pre-grasping location) in new, undemonstrated locations. To fulfill these requirements, a set of control points are selected within the feasible domain. Camera trajectories that traverse these control points are modeled and optimized using either quintic splines (for fast computation) or general polynomials (for better constraint satisfaction). Experiments with a seven degree of freedom articulated arm validate the proposed scheme.
ISSN:0929-5593
1573-7527
DOI:10.1007/s10514-017-9667-4