Real-Time Path Planning in Unknown Environments for Bipedal Robots

Abstract

Autonomous navigation in dynamic and unknown environments requires real-time path planning. Solving the path planning problem for bipedal locomotion quickly and robustly is one of the main challenges in making humanoid robots competitive against mobile platforms. In this letter, we propose strategies to use mobile platform planners for improving the navigation of bipedal robots. These strategies combine advantageously continuous two-dimensional (2-D) paths with conventional step planners for humanoid robots. We introduce a mobile platform planner suitable for real-time navigation. It searches for multiple 2-D paths that makes the path planning more robust against limited calculation time and changing scenarios. It is combined with a step planner and integrated in the framework for autonomous navigation of our robot Lola. We evaluate different strategies in simulation and validate them in experiments in unknown dynamic environments.