ICRA 2012 Paper Abstract

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Paper WeB07.4

Zhang, Yajia (Indiana University Bloomington), Luo, Jingru (Indiana University Bloomington), Hauser, Kris (Indiana University)

Sampling-Based Motion Planning with Dynamic Intermediate State Objectives: Application to Throwing

Scheduled for presentation during the Regular Session "Sampling-Based Motion Planning" (WeB07), Wednesday, May 16, 2012, 11:15−11:30, Meeting Room 7 (Remnicha)

2012 IEEE International Conference on Robotics and Automation, May 14-18, 2012, RiverCentre, Saint Paul, Minnesota, USA

This information is tentative and subject to change. Compiled on October 19, 2017

Keywords Motion and Path Planning, Manipulation Planning, Grasping

Abstract

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 is greatly improved using optimizations based on the fact that ramp-up and ramp-down subproblems are coupled by the choice of intermediate state, and that 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.

 

 

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