发表机构
The Pennsylvania State University; AlphaZ Inc.（宾夕法尼亚州立大学; AlphaZ公司）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对移动机械臂在人类环境中穿越 doorway 的需求，提出基于非线性 MPC 的耦合系统运动规划框架，经仿真与硬件实验验证可生成无碰撞的 door 穿越轨迹。
AI 中文摘要
在人类环境中作业的移动机械臂，穿越 doorway 是一项基础能力，需要移动基座与机械臂末端执行器的协同运动。本文提出一种运动规划框架，可生成动态可行且无碰撞的轨迹，用于自主开启并穿越推式和拉式 door。该方法将机器人与 door 建模为耦合动力系统，纳入非线性模型预测控制（MPC）优化框架；通过基于惩罚的约束确保操作可行性，规划器无需显式建模机械臂运动学。仿真与硬件实验表明，该方法能成功规划 door 穿越的可行轨迹。
英文摘要
Navigating doorways is a fundamental capability for mobile manipulators operating in human environments, requiring coordinated motion between the mobile base and manipulator arm. This paper presents a motion planning framework that generates dynamically feasible and collision-free trajectories for autonomously opening and traversing both push and pull doors. The proposed method formulates the robot and door as a coupled dynamical system within a nonlinear Model Predictive Control (MPC) optimization framework. Manipulation feasibility is enforced through a penalty-based constraint, avoiding explicit arm kinematic modeling in the planner. Simulations and a hardware experiment demonstrate that the approach successfully plans feasible trajectories for door traversal.
