Real-time global path planning for mobile robots with a complex 3-D shape in large-scale 3-D environment

Real-time global path planning in a large-scale dynamic environment for mobile robots is a complex task, especially when the 3-D configurations of the mobile robots and obstacles are considered. There is an existing method for real-time path planning for fixed manipulators in a small field that uses a parallel version of 3-D collision detection to enable/disable edges of a prior generated probabilistic roadmap when the environment is dynamically changing. In this research, we modify the state-of-the-art method to adapt to the global path planning of the mobile robot. We propose a hierarchical probabilistic roadmap to adapt to a large-scale environment. Finally, the real-world experiment is carried out to demonstrate that a mobile robot with a complex 3-D shape can navigate itself in a complex environment with pipes. And another simulation experiment is carried out to prove that the proposed method takes 0.15 s to calculate the global path in a large-scale environment which is a 100-meter square field.