A multi-agent framework for grasping using visual servoing and collision avoidance

This paper describes a multi-agent approach to grasping that combines collision avoidance and visual servoing strategies. Control of the system is distributed among five different types of agents: link agents, joint agents, end-effector agents, task agents, and object agents. As each agent attempts to achieve a desired individual behavior, the manipulator itself exhibits an emergent behavior that avoids obstacles while approaching an object to be grasped. As the object is approached, object agents that represent the object to be grasped and the gripper performing the grasp are instantiated. The instantiation of each of these two object agents, which are guided by visual feedback, automatically changes the manipulator control structure. Once both object agents become active, closed-loop visual servoing of the end-effector during the final stage of grasping is realized. Experimental results are presented that illustrate the three types of manipulator control realized during a typical grasping task