S-BRRT*: A Spline-based Bidirectional RRT with Strategies under Nonholonomic Constraint

Global path planning in more general scene under the constraint condition has always been the difficulty in the field of path planning. Rapidly-exploration Random Tree and its derived algorithm (RRTs) is a popular planning algorithm of path planning in recent years, which is especially suitable for constrained conditions. A feasible path should consider the model and constraints of its execution object. To this end, we propose S-BRRT*: First, a bidirectional spanning tree is introduced into the basic RRT*. Second, nonholonomic constraints are considered into the program, including internal motion constraints and external collision constraints. Then, a new pruning strategy is put forward to conduct intelligent pruning of BRRT*'s zigzag path, including pruning under collision constraint and pruning under path constraint, so as to select optimal path nodes. Finally, the smooth strategy is proposed, using cubic Bézier curve to fitting the previous pruning path for the first time. Then, we fitting for the second time under collision optimization to ensure the final feasibly smooth path. Our S-BRRT * algorithm can realize the global path planning in a variety of scenarios. It is verified by experiments in sparse common scene as well as the scenarios with dense narrow path. We can conclude that the trajectory maintains robust and conforms to the nonholonomic constraints, meanwhile, we obtain improvement in length and feasibility.