SurGE: サロゲート勾配誘導進化による並列弾性を備えた脚ロボットの協調設計
SurGE: Surrogate Gradient-guided Evolution for Co-design of Legged Robots with Parallel Elasticity
脚ロボットの弾性要素を含む協調設計を、微分可能なパイプラインから得たサロゲート勾配をCMA-ESに注入して効率化するフレームワークを提案し、シミュレーションと実機で性能を実証した。
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著者: Yulun Zhuang, Yue Qin, Justin Lu, Zelin Shen, Yichen Wang, Sicheng He, Yanran Ding
分類: cs.RO
原文アブストラクト
Co-design of legged robots with elastic elements is challenging due to the non-differentiability of contact dynamics and mechanism engagement. This paper presents SurGE, a framework that computes surrogate gradients of the design objective through a differentiable pipeline consisting of a kinodynamic single-rigid-body (Kino-SRB) model and a design-aware control policy, and injects them into CMA-ES via mean shift with cosine-annealed step decay. On a 4-DOF design space of a hopping robot with unidirectional parallel spring, SurGE achieves 6 times lower cross-seed standard deviation and 18% tighter population concentration compared to vanilla CMA-ES, while matching or improving the best objective. Hardware experiments on a 2D design subspace show that, starting from a hand-tuned initial design, SurGE reduces the design objective by 37.65% on hardware, with the improvement trend identified in simulation transferring consistently to the physical system. SurGE provides the potential to accelerate non-differentiable co-design problems in legged robots via surrogate model gradients.
