Integrated Motion Planning for Assembly Task with Part Manipulation Using Re-Grasping

Abstract

This paper presents an integrated planner based on rapidly exploring random tree (RRT) for an assembly task with possible re-grasping. Given multiple grasp poses for the part to assemble, the planner chooses candidate grasp poses considering the environment (including the partially finished assembly) in addition to the initial and final poses of the part. Orientation graph search based re-grasping approach is proposed for part manipulation which is needed when there is no feasible grasp solution for a part between its initial and final poses. Orientation graph search helps finding a series of the intermediate poses of the part needed between its initial and final poses so that robot can grasp and assemble it without interfering the pre-assembled parts. Then while extending the tree, the algorithm tries to connect the tree to a robot configuration with a chosen candidate grasp pose. Also, since the task space undergoes changes at each step of the assembly task, a node or edge in the tree can become in collision during the assembly of later parts, making the node in collision and its descendant nodes disconnected from the whole tree. To handle this, Two stage extended RRT strategy is proposed. The disconnected parts of the main tree are put into forest, and attempts are made to re-connect the tree in the forest to main tree while extending the main tree, thus making it possible to use the disconnected part again. The algorithm is implemented in Linux based system using C++. The proposed algorithm is demonstrated experimentally using UR5e robot manipulator by assembling the soma puzzle pieces in different 3D formations.

Semi-Autonomous Behaviour Tree-Based Framework for Sorting Electric Vehicle Batteries Components

“…Assembly and disassembly tasks can be highly beneficial if different candidate grasps and re-grasp poses are considered. For instance, in [21] the authors developed a grasping RRT-based planner to simultaneously find the best grasping and place pose of an assemble part as well as the collision-free path between the initial and final pose. Furthermore, they introduced an orientation graph search-based method to find intermediate poses if the initial pose of a part needs to be reoriented and re-grasped to be assembled.…”

Industry 4.0 and Prospects of Circular Economy: A Survey of Robotic Assembly and Disassembly

“…Moreover, in the case of disconnections from the tree, which may happen to a node and its descendants due to the collisions taking place because of the changes in the task space over each step of assembly, the connection needs to be reestablished for further extension of the tree. This could be realized using algorithms such as the two-stage extended Rapidly-exploring Random Trees [66].…”

High-Speed Autonomous Robotic Assembly Using In-Hand Manipulation and Re-Grasping

“…Recently, there have been a number of works using the Soma cube assembly task as a demonstration [10][11][12][13][14]. The Soma cube assembly task is a good benchmark task for robotic assembly as it has nontrivial number of possible assembly solutions and grasp plans, yet most of the assembly can be realized using a single robotic manipulator.…”