Adaptive attitude design with risk-sensitive optimal feedback control in physical human-robot interaction

Anticipatory behavior based on the human behavior prediction enables the robot to improve the quality of its assistance in physical human-robot interaction (pHRI). However, predictions are partly afflicted with high uncertainties originating from the intrinsic variability in human behavior and the influence of the environment, requiring an attitude negotiation among partners. In this paper, we propose a novel control approach that dynamically adapts the robot's attitude to the disagreement level and the environmental situation in real time facilitating the negotiation between the human and the robot. The approach is based on risk-sensitive optimal feedback control. The adaptive design of the robot's attitude is realized through a dynamical changing risk-sensitivity parameter. The proposed approach is experimentally validated in a cooperative transport scenario in a two-dimensional visuo-haptic virtual environment.