Fast Motion Planning for Non-Holonomic Mobile Robots via a Rectangular Corridor Representation of Structured Environments
🤖 AI Summary
This work addresses the challenge of inefficient motion planning and excessively large search spaces for nonholonomic mobile robots operating in complex structured environments. To this end, the authors propose a rectangular corridor graph representation based on deterministic free-space decomposition. By constructing a compact yet overlapping set of rectangular corridors, the method significantly reduces the search space while preserving path resolution completeness. Integrating efficient graph-based search with analytical trajectory generation, the framework enables near-time-optimal navigation that respects kinematic constraints. Extensive experiments on both large-scale simulations and physical robot platforms demonstrate the approach’s efficiency and practicality, and the implementation has been made publicly available.
Application Category
📝 Abstract
We present a complete framework for fast motion planning of non-holonomic autonomous mobile robots in highly complex but structured environments. Conventional grid-based planners struggle with scalability, while many kinematically-feasible planners impose a significant computational burden due to their search space complexity. To overcome these limitations, our approach introduces a deterministic free-space decomposition that creates a compact graph of overlapping rectangular corridors. This method enables a significant reduction in the search space, without sacrificing path resolution. The framework then performs online motion planning by finding a sequence of rectangles and generating a near-time-optimal, kinematically-feasible trajectory using an analytical planner. The result is a highly efficient solution for large-scale navigation. We validate our framework through extensive simulations and on a physical robot. The implementation is publicly available as open-source software.
Problem
Research questions and friction points this paper is trying to address.
motion planning
non-holonomic robots
structured environments
search space complexity
scalability
Innovation
Methods, ideas, or system contributions that make the work stand out.
rectangular corridor representation
non-holonomic motion planning
free-space decomposition
analytical trajectory generation
structured environments
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