Regrasp Planning Using Stable Object Poses Supported by Complex Structures

Using regrasp planning, a robot could pick up an object, place it down to an intermediate stable state, and reorient the object into certain poses by grasping and picking it up again. Regrasp is an important skill when a robot cannot reorient the object directly with one grasp due to kinematic constraints and collisions. It uses intermediate object states to release, regrasp, and reorient objects. In our previous work, we developed regrasp algorithms considering intermediate stable states on simple fixtures like a flat table surface. This paper further develops our previous studies by enabling regrasp planning using stable object poses on complex structures. The complex structures have high variety of contact elements. They not only provide flat surface supports but also point supports, line supports, and a combination of them. In detail, the developed regrasp planner includes two parallel processes. One is a dynamic simulator that computes immediate stable poses on given supporting structures. The other builds a regrasp graph using the stable states and finds a sequence of reorient motion by searching the graph. We performed thousands of simulation and real-world verification to analyze the performance of the developed planner. We conclude that our planner has higher performance on regrasping than the previous ones. The number of candidate regrasp sequences increased and the lengths became shorter. We also compared simulation results with real-world executions, and gave suggestions on the selection of supporting structures considering real-world implementations.