Addressing pose uncertainty in manipulation planning using task space regions

  • Authors:

  • Dmitry Berenson;Siddhartha S. Srinivasa;James J. Kuffner

  • Affiliations:

  • The Robotics Institute, Carnegie Mellon University, Pittsburgh, PA;Intel Research Pittsburgh, Pittsburgh, PA and The Robotics Institute, Carnegie Mellon University, Pittsburgh, PA;The Robotics Institute, Carnegie Mellon University, Pittsburgh, PA

  • Venue:
  • IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
  • Year:
  • 2009

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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.