Human-Robot Collaborative Planning for Navigation Based on Optimal Control Theory

Navigation modules are capable of driving a robotic platform without direct human participation. However, for some specific contexts, it is preferable to give the control to a human driver. The human driver participation in the robotic control process when the navigation module is running raises the share control issue. This work presents a new approach for two agents collaborative planning using the optimal control theory and the three-layer architecture. In particular, the problem of a human and a navigation module collaborative planning for a trajectory following is analyzed. The collaborative plan executed by the platform is a weighted summation of each agent control signal. As a result, the proposed architecture could be set to work in autonomous mode, in human direct control mode or in any aggregation of these two operating modes. A collaborative obstacle avoidance maneuver is used to validate this approach. The proposed collaborative architecture could be used for smart wheelchairs, telerobotics and unmanned vehicle applications.