Abstract-We present an efficient approach to generating paths for a robotic manipulator that are collision-free and guaranteed to meet task specifications despite pose uncertainty. We first describe how to use Task Space Regions (TSRs) to specify grasping and object placement tasks for a manipulator. We then show how to modify a set of TSRs for a certain task to take into account pose uncertainty. A key advantage of this approach is that if the pose uncertainty is too great to accomplish a certain task, we can quickly reject that task without invoking a planner. If the task is not rejected we run the IKBiRRT planner, which trades-off exploring the robot's C-space with sampling from TSRs to compute a path. Finally, we show several examples of a 7-DOF WAM arm planning paths in a cluttered kitchen environment where the poses of all objects are uncertain.
Berenson et al. REF used Task Space Regions (TSRs) and modified them to handle pose uncertainty.
Addressing pose uncertainty in manipulation planning using Task Space Regions
2009 IEEE/RSJ International Conference on Intelligent Robots and Systems
2009 IEEE/RSJ International Conference on Intelligent Robots and Systems
Computer Science