Seeking Human Help to Manage Plan Failure Risks in Semi-Autonomous Mobile Manipulation

Abstract

Abstract We present a framework for identifying, communicating, and addressing risk in shared-autonomy mobile manipulator applications. This framework is centered on the capacity of the mobile manipulator to sense its environment, interpret complex and cluttered scenes, and estimate the probability of actions and configuration states that may result in task failures, such as collision (i.e., identifying “risk”). If the threshold for acceptable risk is exceeded, a remote operator is notified and presented with timely, actionable information in which the person can quickly assess the situation and provide guidance for the robot. This framework is demonstrated with a use case in which a mobile manipulator performs machine tending and material handling tasks.