A Mixed-Initiative Haptic Teleoperation Strategy for Mobile Robotic Systems Based on Bidirectional Computational Trust Analysis

Abstract

The goal of this paper is to improve the performance of joint human-robot systems while balancing human experience through computational trust analysis in telerobotics applications. A mixed-initiative approach is enabled by scaling the manual and autonomous controls using a function of computational human-to-robot trust. A dynamic haptic force feedback scaling strategy is performed via a function of computational robot-to-human trust to adjust the assistive force and, hence, physical workload of the operator. Passivity-based methods are used to guarantee the stability of the overall framework. Moreover, guidelines are provided to adjust the transparency of force feedback and velocity signals while guaranteeing passivity. An experimental study with 30 human subjects demonstrates a 12.8% increase in task performance and a 10.7% decrease in operator workload when the proposed strategy is used as compared to a manual autonomy allocation approach. The results also indicate that the proposed method yields higher operator satisfaction compared to manual and optimal autonomy allocation methods and is 10.1% more trusted by the operators than the optimal allocation method.