Balancing safety with computational speed is a persistent challenge in autonomous navigation. While optimal pathfinders like A* are efficient, they fail to define the navigable “buffer” zone required for safe motion. Existing corridor generation methods attempt to bridge this gap but often suffer from heavy computational overhead or geometric instability. This paper introduces the Manhattan d-corridor, a framework that constructs strictly bounded, collision-free regions around a reference path. By combining systematic expansion with topological pruning, the algorithm guarantees structural minimality without sacrificing coverage. Experiments confirmed that the method is over two orders of magnitude faster than standard baselines. Crucially, while traditional methods suffered geometric collapse at high resolutions and dropped to unsafe collision ratios, the d-corridor maintained invariant safety (1.0) across all tests. This establishes the framework as a highly robust, real-time solution for resource-constrained robotics.
Yeh et al. (Sat,) studied this question.