A robust and deadlock free navigation of mobile robots based on a task-level feedback control

Abstract

Introduces a methodology that will allow robots to execute tasks autonomously and with a high degree of success. Taking as an example the mobility of a robot without collision in a dynamic environment, a task-level feedback control system is proposed. The key idea is to incorporate the real-time recognition and motion planning functions into the task control loop. For real-time recognition of the environment, mark-based vision is used. In addition, algorithm to do a global motion planning in the environment where movable obstacles exist is proposed. By integrating the real-time recognition and motion planning, we succeed in forming a control loop, for a robust and deadlock free navigation.