Multi-Agent Lane Optimization in Cluttered Environments

Publication Date

1-1-2025

Document Type

Conference Proceeding

Publication Title

2025 11th International Conference on Mechatronics and Robotics Engineering Icmre 2025

DOI

10.1109/ICMRE64970.2025.10976314

First Page

161

Last Page

168

Abstract

Path planning and optimization play an important role in robotics and autonomous vehicles. In this work we address the particular problem of optimizing sets of non-overlapping paths which form lanes for the efficient flow of multiple agents in a given cluttered environment. The proposed method is based on a convex optimization formulation applied to a piecewise Quadratic Bezier path representation. Our method guarantees a given minimum clearance value while minimizing total length and maximum curvature. Clearance is addressed with respect to both obstacles and adjacent lanes, such that a non-overlapping set of lanes is obtained. The proposed method is based on interleaving the optimization of individual lanes according to a priority criterion that improves overall convergence. Users have the flexibility to customize the objective function by assigning different weights to the clearance, length, and curvature objective terms. We present results applied to sets of lanes generated by an RRT planner which has been extended to produce multiple initial lanes. Our results showcase the ability to produce different sets of lanes reflecting user-defined weights. We also present comparisons against a heuristic shortcut-based smoothing method and a generalized optimization formulation, which demonstrate the improved performance of the proposed approach.

Keywords

Convex Optimization, Multi-agent Path Optimization, Path Planning, Piecewise Quadratic Bézler Path

Department

Computer Science

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