Trust-based leader selection for bilateral haptic teleoperation of multi-robot systems

Mutli-robot teleoperation systems benefit from human's capabilities in adaptation to new environments and decision-making in the presence of uncertainty and complexity. In these applications, usually a human operator determines the general behaviour of the multi-robot team via selecting and controlling a leader robot while the follower robots coordinate with the team autonomously. Trust is a major factor in human's allocation of autonomy among the team of robots. A trust-based online leader selection strategy is proposed in this work for multi-robot bilateral haptic teleoperation with applications in collective position tracking and synchronization. Human-to-robot trust is computed and utilized as a dynamic criterion to select the leader. Also, robot-to-human trust is used to dynamically scale the haptic force feedback cues so that the operator receives smaller force feedback when his/her performance in leading the team is higher. This reduces the physical workload of the operator. Due to the trust-based leader switching and force feedback scaling, the stability of the closed-loop system may be lost. We guarantee this stability via passivity-based techniques. Finally, our experimental results indicate that the trust-based leader selection strategy can reduce task completion time by 35.25% and formation error by 41.64% compared to a non-leader switching strategy.

[1]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[2]  Masayuki Fujita,et al.  Passivity-based bilateral human-swarm-interactions for cooperative robotic networks and human passivity analysis , 2015, 2015 54th IEEE Conference on Decision and Control (CDC).

[3]  N Moray,et al.  Trust, control strategies and allocation of function in human-machine systems. , 1992, Ergonomics.

[4]  Radha Poovendran,et al.  Leader selection games under link noise injection attacks , 2012, HiCoNS '12.

[5]  John R. Wagner,et al.  Trust-based mixed-initiative teleoperation of mobile robots , 2016, 2016 American Control Conference (ACC).

[6]  Jun Zhao,et al.  Dissipativity Theory for Switched Systems , 2005, CDC 2005.

[7]  L. Toledo-Pereyra Trust , 2006, Mediation Behaviour.

[8]  Magnus Egerstedt,et al.  Haptic interactions with multi-robot swarms using manipulability , 2015, HRI 2015.

[9]  Magnus Egerstedt,et al.  Executive decision support , 2009, IEEE Robotics & Automation Magazine.

[10]  Jean-Jacques E. Slotine,et al.  Stable Adaptive Teleoperation , 1990, 1990 American Control Conference.

[11]  W. Marsden I and J , 2012 .

[12]  Frank L. Lewis,et al.  Trust method for multi-agent consensus , 2012, Defense, Security, and Sensing.

[13]  John R. Wagner,et al.  A Mixed-Initiative Haptic Teleoperation Strategy for Mobile Robotic Systems Based on Bidirectional Computational Trust Analysis , 2017, IEEE Transactions on Robotics.

[14]  Magnus Egerstedt,et al.  Leader selection via the manipulability of leader-follower networks , 2012, 2012 American Control Conference (ACC).

[15]  Dongjun Lee,et al.  Bilateral Teleoperation of Multiple Cooperative Robots over Delayed Communication Networks: Theory , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[16]  Naomi Ehrich Leonard,et al.  Integrating human and robot decision-making dynamics with feedback: Models and convergence analysis , 2008, 2008 47th IEEE Conference on Decision and Control.

[17]  Gregory Dudek,et al.  OPTIMo: Online Probabilistic Trust Inference Model for Asymmetric Human-Robot Collaborations , 2015, 2015 10th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[18]  Angelika Peer,et al.  Exploring the Design Space of Haptic Assistants: The Assistance Policy Module , 2013, IEEE Transactions on Haptics.