生成可变形陆地机器人,兼具软体与骨骼优势。
Generating Freeform Endoskeletal Robots
- 用弹性与刚性细胞构建内外一体化的机器人结构。
- 通过进化策略在非凸潜空间中优化设计,生成高效移动机器人。
- 适合研究进化设计与层次化具身系统的学习算法。
具身智能体(如机器人)的自动设计已有31年历史,近年来再度受到关注。然而,现有研究仍局限于两类解剖结构简单的机器人:(1) 完全刚性、带关节的结构;(2) 完全柔软、无关节的结构。本文提出一种开放式的陆地内骨骼机器人生成方法:可变形软体结构结合关节式内部骨架,实现高效陆地运动。通过以下步骤实现:(i) 将3D内骨骼构型建模为弹性与刚性细胞直接连接形成的软组织,锚定于复合刚性体;(ii) 将这些离散机械子系统编码为连续而一致的潜在嵌入;(iii) 使用无模型强化学习优化每种设计的感知-运动协调;(iv) 利用进化策略在平滑但高度非凸的潜在流形上导航。该方法持续生成新型“高级机器人”,其兼具弹性组织与骨骼杠杆的机械优势,类比高等动物的运动机制。同时,提供一个即插即用的实验平台,用于基准测试复杂层次化具身系统中的进化设计与表征学习算法。
原文摘要 · Abstract (English)
The automatic design of embodied agents (e.g. robots) has existed for 31 years and is experiencing a renaissance of interest in the literature. To date however, the field has remained narrowly focused on two kinds of anatomically simple robots: (1) fully rigid, jointed bodies; and (2) fully soft, jointless bodies. Here we bridge these two extremes with the open ended creation of terrestrial endoskeletal robots: deformable soft bodies that leverage jointed internal skeletons to move efficiently across land. Simultaneous de novo generation of external and internal structures is achieved by (i) modeling 3D endoskeletal body plans as integrated collections of elastic and rigid cells that directly attach to form soft tissues anchored to compound rigid bodies; (ii) encoding these discrete mechanical subsystems into a continuous yet coherent latent embedding; (iii) optimizing the sensorimotor coordination of each decoded design using model-free reinforcement learning; and (iv) navigating this smooth yet highly non-convex latent manifold using evolutionary strategies. This yields an endless stream of novel species of "higher robots" that, like all higher animals, harness the mechanical advantages of both elastic tissues and skeletal levers for terrestrial travel. It also provides a plug-and-play experimental platform for benchmarking evolutionary design and representation learning algorithms in complex hierarchical embodied systems.
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