用模型预测控制协调机械臂与底盘，实现自动开关门。
Motion Planning for Mobile Manipulators Navigating Doorways via Model Predictive Control
- 将机器人与门视为耦合系统，在非线性MPC中联合规划运动。
- 无需显式建模机械臂运动学，通过惩罚项保证操作可行性。
- 仿真与实验证明可生成避障且动态可行的过门轨迹。
在人类环境中运行的移动操作机器人，穿越门洞是一项基本能力，需协调移动底盘与机械臂的运动。本文提出一种运动规划框架，可自动生成动态可行且无碰撞的轨迹，实现对推拉门的自主开启与穿越。该方法将机器人与门建模为耦合动力系统，嵌入非线性模型预测控制（MPC）优化框架中。通过基于惩罚的约束来保证操作可行性，避免在规划器中显式使用机械臂运动学模型。仿真与硬件实验表明，该方法能成功规划出适用于门洞穿越的可行轨迹。
原文摘要 · Abstract (English)
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.
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