发表机构
Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出一种任务导向的齿轮执行器协同设计优化框架，联合优化硬件与控制，实验表明其扭矩密度比商用执行器高60%、重量轻18.6%。
AI 中文摘要
腿式机器人执行的不同任务对执行器提出了不同的扭矩和速度要求。现有的机器人执行器通常在组件层面针对扭矩或功率密度等指标进行优化，缺乏明确的任务导向。由于计算成本高以及机械、电气和电磁行为之间的耦合，跨电机、齿轮箱和传感器等组件的系统级优化具有挑战性。因此，单个组件的改进可能无法转化为特定任务中机器人性能的提升。为此，我们提出了一种系统化的优化框架，用于执行器硬件与控制的任务导向型协同设计。首先，采用代理模型来加速电机评估并支持对耦合设计空间的全局探索。然后，采用分层混合变量优化策略，将离散枚举与连续搜索相结合，涵盖尺寸和实值索引。这些索引在每次评估前被取整，以选择剩余离散选项的允许值。在此搜索中，额定输出扭矩密度和任务性能被联合优化，并为每个硬件候选确定贝塞尔参数化的关节扭矩曲线。最后，通过执行器制造和两自由度跳跃腿实验验证了所提框架的有效性。根据其测量质量，制造的原型实现了35.7 N·m/kg的额定输出扭矩密度，比广泛使用的商用齿轮关节执行器高出约60%，同时重量轻18.6%。在匹配的台架条件下，它在两倍额定扭矩下实现了12.0%更高的跳跃高度。这些结果共同展示了一条从任务需求到执行器设计和控制的系统化路径。
英文摘要
Different tasks performed by legged robots impose distinct torque and speed requirements on actuators. Existing robotic actuators are generally optimized at the component level for metrics such as torque or power density, without explicit task guidance. System-level optimization across components such as motors, gearboxes, and sensors is challenging because of the high computational cost and coupling among mechanical, electrical, and electromagnetic behaviors. Consequently, improvements in individual components may not translate into better robot performance in a specific task. To this end, we present a systematic optimization framework for task-oriented co-design of actuator hardware and control. First, surrogate models are employed to accelerate motor evaluation and support global exploration of the coupled design space. Then, a hierarchical mixed-variable optimization strategy is adopted, combining discrete enumeration with continuous search over dimensions and real-valued indices. These indices are rounded to select admissible values for the remaining discrete choices before each evaluation. Within this search, rated output torque density and task performance are jointly optimized, with Bezier-parameterized joint torque profiles determined for each hardware candidate. Finally, the effectiveness of the proposed framework is validated through actuator fabrication and experiments on a two-degree-of-freedom jumping leg. Based on its measured mass, the fabricated prototype achieves a nominal rated output torque density of 35.7 N m/kg, approximately 60% higher than that of a widely used commercial geared joint actuator, while being 18.6% lighter. Under matched bench conditions, it achieves 12.0% greater jump height at twice-rated torque. Together, these results demonstrate a systematic route from task requirements to actuator design and control.
