Sliding autonomy for complex coordinated multi-robot tasks: Analysis and experiments

Abstract

Autonomous systems are efficient but often unreliable. In domains where reliability is paramount, efficiency is sacrificed by putting an operator in control via teleoperation. We are investigating a mode of shared control called "Sliding Autonomy" that combines the efficiency of autonomy and the reliability of human control in the performance of complex tasks, such as the assembly of large structures by a team of robots. Here we introduce an approach based on Markov models that captures interdependencies between the team members and predicts system performance. We report results from a study in which three robots work cooperatively with an operator to assemble a structure. The scenario requires high precision and has a large number of failure modes. Our results support both our expectations and modeling and show that our combined robot-human team is able to perform the assembly at a level of efficiency approaching that of fully autonomous operation while increasing overall reliability to near-teleoperation levels. This increase in performance is achieved while simultaneously reducing mental operator workload.