A path planning strategy for searching the most reliable path in uncertain environments

Abstract

A path planning method for searching the most reliable path in uncertain environments is proposed in this article. When a robot chases a target in a semi-structured workspace with hazards and uncertainty, which path it takes is of great matter as different paths can lead to diverse risks. To "enlighten" the robot on a wiser choice, a reliability-based topological map is built, in which it is possible to add uncertainty information such as threats and road condition to topological nodes. With this map, the robot is possible to minimize risks in carrying out a target search task. Further simulation and physical-world experiments indicate that the most reliable path method generates a path a bit longer, following which the robot encounters less risks.