Multi-Agent Perception for Human/Robot Interaction: A Framework for Intuitive Trajectory Modification

Abstract

An application of distributed perception to a novel human/computer interface is presented. A multi-agent network has been applied to the task of modifying a robotic trajectory based on very sparse physical inputs from the user. The user conveys intentions by nudging the end effector, instrumented with a wrist force/torque sensor, in an intuitive manner. In response, each agent interprets these sparse inputs with the aid of a local, fuzzified, heuristic model of a particular parameter or trajectory shape. The agents then independently determine the confidence of their respective findings and distributed arbitration resolves the interpretation through voting.