An Autonomous Behavior Switching Method for Indoor Mobile Service Robots

The motion planning for human-robot coexisting scenarios requires indoor service robots to autonomously optimize their behaviors by comprehensively considering the constraints of the corresponding service situation. Those constraints include the semantic map of the workplace, desired optimization objective, human's comfort feelings, etc. Due to the constraints of different service situations shall differ from each other, the improvement of indoor service robots' ability of autonomous decision-making is key to the motion planning for human-robot coexisting scenarios. This paper designs a ROS-based autonomous behavior switching method so that a robot can switch its motion planning algorithms according to different service situations. Simulation results verified that the designed method made the robot switch its motion planning algorithms without human's intervention.