Trajectory filtering and prediction for automated tracking and grasping of a moving object
- Trajectory filtering and prediction for automated tracking and grasping of a moving object
- Allen, Peter K.
- Computer Science
- Persistent URL:
- Book/Journal Title:
- Proceedings : 1992 IEEE International Conference on Robotics and Automation, May 12-14, 1992, Nice, France
- Publisher Location:
- Los Alamitos, Calif.
- The authors explore the requirements for grasping a moving object. This task requires proper coordination between at least three separate subsystems: real-time vision sensing, trajectory-planning/arm-control, and grasp planning. As with humans, the system first visually tracks the object's 3D position. Because the object is in motion, this must be done in real-time to coordinate the motion of the robotic arm as it tracks the object. The vision system is used to feed an arm control algorithm that plans a trajectory. The arm control algorithm is implemented into two steps: filtering and prediction and kinematic transformation computation. Once the trajectory of the object is tracked, the hand must intercept the object to actually grasp it. Experimental results are presented in which a moving model train was tracked, stably grasped, and picked up by the system.
- Publisher DOI:
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- Suggested Citation:
- Peter K. Allen, Aleksandar Timcenko, Billibon Yoshimi, Paul Michelman, 1992, Trajectory filtering and prediction for automated tracking and grasping of a moving object, Columbia University Academic Commons, https://doi.org/10.7916/D8RB7DV4.