Addressing Pose Uncertainty in Manipulation Planning Using Task Space Regions - Robotics Institute Carnegie Mellon University

Addressing Pose Uncertainty in Manipulation Planning Using Task Space Regions

Conference Paper, Proceedings of (IROS) IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1419 - 1425, October, 2009

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.

BibTeX

@conference{Berenson-2009-10342,
author = {Dmitry Berenson and Siddhartha Srinivasa and James Kuffner},
title = {Addressing Pose Uncertainty in Manipulation Planning Using Task Space Regions},
booktitle = {Proceedings of (IROS) IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2009},
month = {October},
pages = {1419 - 1425},
keywords = {manipulation planning, planning with uncertainty, sampling-based planning},
}