优化五杆单足机器人机械、电机与控制，跳得更远更省电。
A Co-Design Framework for High-Performance Jumping of a Five-Bar Monoped with Actuator Optimization
- 联合优化机械结构、电机齿轮箱参数和控制策略，实现动态跳跃性能提升。
- 跳远距离提升30.4%，机械能耗降低11.5%，优于原始设计。
- 适用于需要高能效跳跃的仿生机器人研发，尤其适合闭链机构设计。
腿式机器人的性能高度依赖机械设计与控制策略，促使人们采用联合优化方法协同设计。然而，现有研究多关注连杆尺寸与传动比，忽视了电机与减速箱等执行器参数的详细优化，且主要局限于串联开链机构。本文提出一种针对平面闭链五杆单足机器人的联合设计框架，同步优化机械结构、电机与减速箱参数及控制参数，目标为最大化跳跃距离并最小化机械能耗。框架采用两阶段优化：先通过执行器优化生成齿比到执行器质量、效率和峰值扭矩的映射关系，再将其融入基于CMA-ES的机器人设计与控制联合优化中。仿真结果表明，相比基准设计，跳跃距离提升约30.4%，机械能耗降低11.5%，验证了该框架在实现高性能、高能效平面跳跃方面的有效性。
原文摘要 · Abstract (English)
The performance of legged robots depends strongly on both mechanical design and control, motivating co-design approaches that jointly optimize these parameters. However, most existing co-design studies focus on link dimensions and transmission ratios while neglecting detailed actuator design, particularly motor and gearbox parameter optimization, and are largely limited to serial open-chain mechanisms. In this work, we present a co-design framework for a planar closed-chain five-bar monoped that jointly optimizes mechanical design, motor and gearbox parameters, and control parameters for dynamic jumping. The objective is to maximize jump distance while minimizing mechanical energy consumption. The framework employs a two-stage optimization approach, where actuator optimization generates a mapping from gear ratio to actuator mass, efficiency, and peak torque, which is then incorporated into CMA-ES-based co-design optimization of the robot design and control parameters. Simulation results demonstrate an improvement of approximately 30.4% in jump distance and an 11.5% reduction in mechanical energy consumption compared to a nominal design, highlighting the effectiveness of the proposed framework for high-performance and energy-efficient planar jumping.
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