优化人形机器人结构与控制性能，兼顾可制造性与安全性。
From CAD to URDF: Co-Design of a Jet-Powered Humanoid Robot Including CAD Geometry
- 通过多目标进化算法优化关键部件几何形状以提升控制性能。
- 集成有限元分析筛选出满足安全裕度的机械设计方案。
- 适用于需要高精度控制与复杂机械设计的飞行机器人研发。
传统协同设计通常依赖从CAD中提取的简化模型，虽利于控制参数优化，却可能忽略原型制造中的力学应力和装配复杂性等关键细节。本文提出一种协同设计框架，旨在同时提升机器人控制性能与机械设计质量。具体而言，识别对控制性能影响显著的机器人连杆，对其几何特征进行参数化，并采用多目标进化算法优化以实现最佳控制表现。同时，框架内嵌自动化有限元分析（FEM），用于剔除不满足结构安全裕度的设计方案。该方法应用于喷气驱动人形机器人iRonCub，验证了其在提升飞行性能方面的有效性。
原文摘要 · Abstract (English)
Co-design optimization strategies usually rely on simplified robot models extracted from CAD. While these models are useful for optimizing geometrical and inertial parameters for robot control, they might overlook important details essential for prototyping the optimized mechanical design. For instance, they may not account for mechanical stresses exerted on the optimized geometries and the complexity of assembly-level design. In this paper, we introduce a co-design framework aimed at improving both the control performance and mechanical design of our robot. Specifically, we identify the robot links that significantly influence control performance. The geometric characteristics of these links are parameterized and optimized using a multi-objective evolutionary algorithm to achieve optimal control performance. Additionally, an automated Finite Element Method (FEM) analysis is integrated into the framework to filter solutions not satisfying the required structural safety margin. We validate the framework by applying it to enhance the mechanical design for flight performance of the jet-powered humanoid robot iRonCub.
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