Adaptive State × Time Lattices: A Contribution to Mobile Robot Motion Planning in Unstructured Dynamic Environments

Mobile robot motion planning in unstructured dynamic environments is a challenging task. Thus, often suboptimal methods are employed which perform global path planning and local obstacle avoidance separately. This work introduces a holistic planning algorithm which is based on the concept of state × time lattices with variable dimensionality and multiple resolutions. The adaptive planning method makes it possible to rapidly plan local maneuvers while still pursuing global optimality.