发表机构
Norlab, Université Laval; TSCF, INRAE（拉瓦尔大学Norlab; 法国国家农业、食品与环境研究院TSCF）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究提出有限支撑二次模型（FSQ），通过准静态平衡纳入旋转阻力，推广点接触模型，在7公里实测中使五秒预测误差降低53.5%和68.9%。
AI 中文摘要
野外机器人技术中的轨迹规划与控制依赖于预测当接触点发生滑移时推进和转向对车辆运动的影响。对于铰接式车辆，点接触运动学模型（PCK）考虑了连杆几何形状，但忽略了沿接触点分布的旋转阻力。我们提出了一种用于单履带、中心铰接车辆的有限支撑二次模型（FSQ），该模型通过横向滑移的准静态平衡来纳入这种阻力。我们的方法通过放宽接触点假设，推广了标准的PCK公式。将二次滑移成本精确简化为接触力矩，得到了用于实时预测横向速度和横摆率的紧凑闭式解。我们在沥青、草地、冰面和混合路线上进行了实际实验，使用超过7公里的数据评估了所提出的方法。对于五秒预测，相对于PCK，FSQ将加权中位数平移误差和横摆误差分别降低了53.5%和68.9%。
英文摘要
Trajectory planning and control in field robotics rely on predicting how propulsion and steering affect vehicle motion when contact points undergo slip. For articulated vehicles, the point-contact kinematic model (PCK) accounts for the linkage geometry but neglects the rotational resistance distributed along the contacts. We propose a finite-support quadratic model (FSQ) for single-track, center-articulated vehicles that incorporates this resistance through a quasi-static balance of lateral slip. Our approach generalizes the standard PCK formulation by relaxing the contact-point assumption. An exact reduction of the quadratic slip cost to contact moments gives a compact closed-form solution for real-time prediction of lateral velocity and yaw rate. We evaluate the proposed method in real-world experiments across asphalt, grass, ice, and mixed routes, using more than 7 km of data. For five-second predictions, FSQ reduces the weighted median translation and yaw errors by 53.5% and 68.9%, respectively, relative to PCK.
Comments8 pages, 7 figures, 1 table
