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Sampling-based motion planning with dynamic intermediate state objectives: Application to throwing

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3 Author(s)
Yajia Zhang ; Sch. of Inf. & Comput., Indiana Univ. Bloomington, Bloomington, IN, USA ; Jingru Luo ; Hauser, K.

Dynamic manipulations require attaining high velocities at specified configurations, all the while obeying geometric and dynamic constraints. This paper presents a motion planner that constructs a trajectory that passes at an intermediate state through a dynamic objective region, which is comprised of a certain lower dimensional submanifold in the configuration/velocity state space, and then returns to rest. Planning speed and reliability are greatly improved by finding good intermediate states first, because the choice of intermediate state couples the ramp-up and ramp-down subproblems, and moreover very few (often less than 1%) intermediate states yield feasible solution trajectories. Simulation experiments demonstrate that our method quickly generates trajectories for a 6-DOF industrial manipulator throwing a small object.

Published in:

Robotics and Automation (ICRA), 2012 IEEE International Conference on

Date of Conference:

14-18 May 2012

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