被动关节动力学下的自主砖块装配：集成视觉MPC控制的起重机

本文提出了一种用于建筑环境中执行预制砖块装配的 articulated boom crane 的自主控制框架。所解决的关键挑战是受被动关节动力学导致的摆动在 precise placement control 下造成的困难，这使 accurate positioning of building components 变得复杂。 Our integrated approach combines real-time vision-based pose estimation of building blocks， collision-aware B-spline path planning， and nonlinear model predictive control (NMPC) to achieve autonomous pickup， placement， and obstacle-avoidance assembly operations。 The framework is validated on a laboratory-scale testbed that emulates crane kinematics and passive dynamics while enabling rapid experimentation。 The collision-aware planner generates feasible B-spline references in real-time on CPU hardware with anytime performance， while the NMPC controller actively suppresses passive joint sway and tracks the planned trajectory under continuous vision feedback。 Experimental results demonstrate autonomous block stacking and obstacle-avoidance assembly， with sway damping reducing settling times by more than an order of magnitude compared to uncontrolled passive dynamics， confirming the real-time feasibility of the integrated approach for construction automation。