On the Evolution of Fingertip Grasping Manifolds
2016 (English)In: IEEE International Conference on Robotics and Automation, IEEE Robotics and Automation Society, 2016Conference paper (Refereed)
Efficient and accurate planning of fingertip grasps is essential for dexterous in-hand manipulation. In this work, we present a system for fingertip grasp planning that incrementally learns a heuristic for hand reachability and multi-fingered inverse kinematics. The system consists of an online execution module and an offline optimization module. During execution the system plans and executes fingertip grasps using Canny’s grasp quality metric and a learned random forest based hand reachability heuristic. In the offline module, this heuristic is improved based on a grasping manifold that is incrementally learned from the experiences collected during execution. The system is evaluated both in simulation and on a SchunkSDH dexterous hand mounted on a KUKA-KR5 arm. We show that, as the grasping manifold is adapted to the system’s experiences, the heuristic becomes more accurate, which results in an improved performance of the execution module. The improvement is not only observed for experienced objects, but also for previously unknown objects of similar sizes.
Place, publisher, year, edition, pages
IEEE Robotics and Automation Society, 2016.
Fingertip Grasping, Grasping Manifold
Research subject Computer Science
IdentifiersURN: urn:nbn:se:kth:diva-187060OAI: oai:DiVA.org:kth-187060DiVA: diva2:928843
IEEE International Conference on Robotics and Automation
QC 201605172016-05-162016-05-162016-05-18Bibliographically approved