Fast Near Time-Optimal Motion Planning for Holonomic Vehicles in Structured Environments

2026-02-02

AI Summary

This work addresses the problem of real-time, near time-optimal trajectory generation for omnidirectional mobile vehicles in structured environments. The authors propose a low-dimensional parameterization method based on free-space corridors and motion primitives. By heuristically selecting motion primitives and solving the trajectory optimization problem in a reduced-dimensional space, the approach significantly lowers computational complexity while preserving near time-optimality, thereby enabling efficient real-time replanning. Experimental results on both simulations and a physical Beckhoff XPlanar system demonstrate that the proposed method substantially outperforms existing approaches such as OMG-tools and VP-STO in computational speed, while generating trajectories that closely approximate time-optimal solutions. This advancement enhances operational efficiency and responsiveness in applications such as assembly lines and automated laboratories.

Technology Category

• Intelligent Robots: Motion and Path Planning
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Sampling/Simulation-based Search

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation

Abstract

This paper proposes a novel and efficient optimization-based method for generating near time-optimal trajectories for holonomic vehicles navigating through complex but structured environments. The approach aims to solve the problem of motion planning for planar motion systems using magnetic levitation that can be used in assembly lines, automated laboratories or clean-rooms. In these applications, time-optimal trajectories that can be computed in real-time are required to increase productivity and allow the vehicles to be reactive if needed. The presented approach encodes the environment representation using free-space corridors and represents the motion of the vehicle through such a corridor using a motion primitive. These primitives are selected heuristically and define the trajectory with a limited number of degrees of freedom, which are determined in an optimization problem. As a result, the method achieves significantly lower computation times compared to the state-of-the-art, most notably solving a full Optimal Control Problem (OCP), OMG-tools or VP-STO without significantly compromising optimality within a fixed corridor sequence. The approach is benchmarked extensively in simulation and is validated on a real-world Beckhoff XPlanar system

Problem

• motion planning
• time-optimal trajectories
• holonomic vehicles
• structured environments
• real-time computation

Innovation

• motion primitive
• free-space corridor
• time-optimal trajectory
• holonomic vehicle
• real-time motion planning