Representations for cross-task, cross-object grasp transfer

Martin Hjelm, Renaud Detry, Carl Henrik Ek, Danica Kragic
2014 2014 IEEE International Conference on Robotics and Automation (ICRA)  
We address the problem of transferring grasp knowledge across objects and tasks. This means dealing with two important issues: 1) the induction of possible transfers, i.e., whether a given object affords a given task, and 2) the planning of a grasp that will allow the robot to fulfill the task. The induction of object affordances is approached by abstracting the sensory input of an object as a set of attributes that the agent can reason about through similarity and proximity. For grasp
more » ... , we combine a part-based grasp planner with a model of task constraints. The task constraint model indicates areas of the object that the robot can grasp to execute the task. Within these areas, the part-based planner finds a hand placement that is compatible with the object shape. The key contribution is the ability to transfer task parameters across objects while the partbased grasp planner allows for transferring grasp information across tasks. As a result, the robot is able to synthesize plans for previously unobserved task/object combinations. We illustrate our approach with experiments conducted on a real robot.
doi:10.1109/icra.2014.6907697 dblp:conf/icra/HjelmDEK14 fatcat:qn7aimvx25arfd5nshsg6o5emy