Drivable Path Planning Using Hybrid Search Algorithm Based on E* and Bernstein–Bézier Motion Primitives

Abstract

This article proposes a hybrid path-planning algorithm, the HE* algorithm, which combines the discrete grid-based E* search and continuous Bernstein–Bézier (BB) motion primitives. Several researchers have addressed the smooth path planning problem and the sample-based integrated path planning techniques. We believe that the main benefits of the proposed approach are: directly drivable path, no additional post-optimization tasks, reduced search branching, low computational complexity, and completeness guarantee. Several examples and comparisons with the state-of-the-art planners are provided to illustrate and evaluate the main advantages of the HE* algorithm. HE* yields a collision-safe and smooth path that is close to spatially optimal (the Euclidean shortest path) with a guaranteed continuity of curvature. Therefore, the path is easily drivable for a wheeled robot without any additional post-optimization and smoothing required. HE* is a two-stage algorithm which uses a direction-guiding heuristics computed by the E* search in the first stage, which improves the quality and reduces the complexity of the hybrid search in the second stage. In each iteration, the search is expanded by a set of BBs, the parameters of which adapt continuously according to the guiding heuristics. Completeness is guaranteed by relying on a complete node mechanism, which also provides an upper bound for the calculated path cost. A remarkable feature of HE* is that it produces good results even at coarse resolutions.