通过简化模型优化机器人轨迹，节能可达15%且更易部署。
Energy Consumption in Robotics: A Simplified Modeling Approach
- 用可微分动力学模型结合标准ROS规划工具
- 简化模型在协作机器人上实现90%以上精度
- 适合工业界快速集成到现有机器人系统
机器人的能耗依赖于运动轨迹，通过轨迹优化可降低能耗。现有方法在固定起点和终点下最多可节省15%能耗，但在工业机器人规划中应用受限，主要因模型复杂且难以与碰撞避让等其他规划工具集成。本文提出一种基于开源工具中可微分惯性和运动学模型的方法，与标准ROS规划流程集成。可选地通过单参数电气模型扩展逆动力学能耗模型，简化参数标定过程。在协作机器人上对比惯性与电气模型，结果表明简化模型具备竞争力的精度，且更易于实际部署。
原文摘要 · Abstract (English)
The energy use of a robot is trajectory-dependent, and thus can be reduced by optimization of the trajectory. Current methods for robot trajectory optimization can reduce energy up to 15\% for fixed start and end points, however their use in industrial robot planning is still restricted due to model complexity and lack of integration with planning tools which address other concerns (e.g. collision avoidance). We propose an approach that uses differentiable inertial and kinematic models from standard open-source tools, integrating with standard ROS planning methods. An inverse dynamics-based energy model is optionally extended with a single-parameter electrical model, simplifying the model identification process. We compare the inertial and electrical models on a collaborative robot, showing that simplified models provide competitive accuracy and are easier to deploy in practice.
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