Combined trajectory generation and path planning for mobile robots using lattices with hybrid dimensionality

Safe navigation for mobile robots in unstructured and dynamic environments is still a challenging research topic. Most approaches use separate algorithms for global path planning and local obstacle avoidance. However, this generally results in globally sub-optimal navigation strategies. In this paper, we present an algorithm which combines these two navigation tasks in a single integrated approach. For this purpose, we introduce a novel search space, namely, a state×time lattice with hybrid dimensionality. We describe a procedure for generating high-quality motion primitives for a mobile robot with four-wheel steering to define the motion in this lattice. Our algorithm computes a hybrid solution for the path planning problem consisting of a trajectory (i.e., a path with time component) in the imminent future, a dynamically feasible path in the near future, and a kinematically feasible path for the remaining time to the goal. Finally, we provide some results of our algorithm in action to prove its high solution quality and real-time capability.