Multimodal Environment Dynamics for Interactive Robots: Towards Fault Detection and Task Monitoring

Interactive robots offer improved performance in tasks with environmental uncertainty, but accommodating environment input weakens predictions of contact force or position trajectories, making the identification of subtask completion or faults difficult. This paper develops a task monitoring approach for complex assembly tasks that involve transitions between discrete environment dynamic modes. In semi-structured environments, these dynamic modes and their transitions are approximately known a priori, allowing task monitoring through estimation of the current mode and fault detection as a deviation from expected, desired dynamic mode transitions. This allows a more natural description of many interactive tasks, improving robustness to variations in force or position trajectories that impedance control seeks to address. The ability of impedance and admittance controlled robots to identify their environment is investigated, making consideration of joint and end-effector physical compliance. Prior information on environment dynamics and mode transitions allow recursive estimates of dynamic mode suitable for online use, under both full state knowledge and only force/position measurements. Experiments with an admittance controlled robot in a gear assembly task validate the approach.