Abstract
Safe and efficient path planning for mobile robots in dynamic environments is still a challenging research topic. Most approaches use separate algorithms for global path planning and local obstacle avoidance. Furthermore, planning a path for a sequence of goals is mostly done by planning to each next goal individually. These two strategies generally result in sub-optimal navigation strategies. In this paper, we present an algorithm which addresses these problems in a single combined approach. For this purpose, we model the static and dynamic risk of the environment in a consistent way and propose a novel graph structure based on a state × time × goal lattice with hybrid dimensionality. It allows the joint planning for multiple goals while incorporating collision risk due to dynamic and static obstacles. It computes hybrid solutions which are part trajectory and part path. Finally, we provide some results of our algorithm in action to prove its high quality solutions and real-time capability.
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