改进微移动车辆运动规划中的角部裁剪约束，提升轨迹效率与安全性。
Improved Corner Cutting Constraints for Mixed-Integer Motion Planning of a Differential Drive Micro-Mobility Vehicle
- 提出新型采样间碰撞避免约束，优化混合整数线性规划求解。
- 在任务耗时与控制努力上优于两种先进方法，显著提升轨迹质量。
- 适用于城市短途运输场景，适合关注高精度路径规划的工程师。
本文研究差速驱动微型移动平台的运动规划问题，该类车辆专为结构化环境中短距离人员与货物运输设计。通过混合整数线性规划（MILP）方法，计算考虑车辆运动学与动力学特性的全局最优无碰撞轨迹。本文提出新型采样间碰撞避免约束，并通过接送任务与蒙特卡洛模拟的统计分析验证其有效性。结果表明，在任务耗时与控制努力方面，新方法均优于两种现有先进方法，生成了最优轨迹。
原文摘要 · Abstract (English)
This paper addresses the problem of motion planning for differential drive micro-mobility platforms. This class of vehicle is designed to perform small-distance transportation of passengers and goods in structured environments. Our approach leverages mixed-integer linear programming (MILP) to compute global optimal collision-free trajectories taking into account the kinematics and dynamics of the vehicle. We propose novel constraints for intersample collision avoidance and demonstrate its effectiveness using pick-up and delivery missions and statistical analysis of Monte Carlo simulations. The results show that the novel formulation provides the best trajectories in terms of time expenditure and control effort when compared to two state-of-the-art approaches.
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