Humanoid service robots performing complex object manipulation tasks need to plan whole-body motions that satisfy a variety of constraints: The robot must keep its balance, self-collisions and collisions with obstacles in the environment must be avoided and, if applicable, the trajectory of the end-effector must follow the constrained motion of a manipulated object in Cartesian space. We present an approach to whole-body motion planning that is based on rapidly-exploring random trees in combination with inverse kinematics. Using our system, humanoids are able to plan motions so as to open drawer, doors, and picking up objects.
Code will be made available open source in ROS / MoveIt!
- Whole-Body Motion Planning for Manipulation of Articulated Objects.
F. Burget, A. Hornung, and M. Bennewitz.
In: Proceedings of the IEEE International Conference on Robotics & Automation (ICRA), 2013.
The videos below show our Nao humanoids executing computed whole-body motion plans for opening a drawer and a door, reaching into different shelfs of a cabinet, and picking up and placing an object.
Direct link to YouTube
Complete video that also illustrates the goal generation for planning and contains additional challenging planning problems: