仿人手臂运动轨迹规划，让幕墙安装机器人省电近半
Trajectory Planning of a Curtain Wall Installation Robot Based on Biomimetic Mechanisms
- 借鉴人体举哑铃时的发力与能量转换机制设计路径
- 仿真显示能量消耗降低48.4%，动能势能智能转化是关键
- 适合关注建筑机器人节能优化的工程师与研究者
随着机器人市场快速发展，能耗成为制约施工机器人应用的关键问题。本文创新性地借鉴人体上肢负重举起动作的力学原理，提出一种融合人类能量转换规律的生物启发式轨迹规划框架。通过采集哑铃弯举过程中的运动轨迹与肌电（EMG）信号，构建融合人类用力模式与能耗特征的人体仿生轨迹规划模型。利用粒子群优化（PSO）算法，实现基于类人运动特性的机械臂动态负载分配。在幕墙安装任务中验证了该方法的正确性与优越性。仿真结果表明，通过智能实现动能与势能之间的转换，能耗降低48.4%。该方法为幕墙安装机器人实际作业中的能耗优化提供了新思路与理论支持。
原文摘要 · Abstract (English)
As the robotics market rapidly evolves, energy consumption has become a critical issue, particularly restricting the application of construction robots. To tackle this challenge, our study innovatively draws inspiration from the mechanics of human upper limb movements during weight lifting, proposing a bio-inspired trajectory planning framework that incorporates human energy conversion principles. By collecting motion trajectories and electromyography (EMG) signals during dumbbell curls, we construct an anthropomorphic trajectory planning that integrates human force exertion patterns and energy consumption patterns. Utilizing the Particle Swarm Optimization (PSO) algorithm, we achieve dynamic load distribution for robotic arm trajectory planning based on human-like movement features. In practical application, these bio-inspired movement characteristics are applied to curtain wall installation tasks, validating the correctness and superiority of our trajectory planning method. Simulation results demonstrate a 48.4% reduction in energy consumption through intelligent conversion between kinetic and potential energy. This approach provides new insights and theoretical support for optimizing energy use in curtain wall installation robots during actual handling tasks.
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