crossposted from willowgarage.com
Adam Harmat from McGill University worked on three projects this summer to make the PR2 more dexterous when manipulating objects: a monitoring system for arm movement, a persistent 3D collision map, and a multi-table manipulation application. All of these projects demonstrated how increased knowledge of its environment is necessary for improving PR2's mobile manipulation capabilities.
The arm-monitoring system uses head-mounted stereo cameras to detect new obstacles. While the arm moves, the PR2 looks at locations that are a few seconds ahead of the arm's current position. Any detected obstacles are added to a collision map, and, if a future collision is anticipated, the arm stops and waits. If the new obstacle doesn't move, the PR2 will attempt to move around it.
The collision map was improved to store information about everything the robot has previously seen. This allows the PR2 to perform tasks that require it to relocate as it maintains knowledge about places it currently cannot see. This new collision map is based on Octomap, an open source package from the University of Freiburg. The octree structure of Octomap is more compact and also enables the storing of probabilistic values.
No one wants a clumsy robot. As a result of these projects, the PR2 is able to maintain more knowledge about its local environment, and is able to keep its arms from bumping into objects. Adam developed a demo application to demonstrate these new capabilities.
In his multi-table manipulation demo, the PR2 continuously finds and moves objects between separate tables. This application is integrated with the ROS navigation stack to determine pickup locations and navigate between tables. Adam's multi-table application demonstrates how planning with the persistent collision map can be integrated with base movement and local task-execution into a complete system.