arXiv:2409.15187cs.RO2024-09ICRA被引 1

仿生机器人通过局部互动实现自组织旋转,抗故障能力强。

Loopy Movements: Emergence of Rotation in a Multicellular Robot

  • 用化学信号模拟生物机制,无中心控制实现自组织旋转
  • 内部凹陷区旋转更快,细胞与整体形态反向转动
  • 即使三分之一马达失效仍能保持旋转,适合鲁棒系统设计

与多数人工系统不同,许多生物系统依赖低层交互产生涌现行为,从而在复杂动态环境中展现更高多样性与适应性。本研究探索由同质、物理连接的单自由度单元组成的多细胞机器人Loopy中涌现的去中心化旋转现象。受向日葵等生物启发,Loopy通过简单的局部交互——化学物质(形态发生素)的扩散、反应与主动运输——实现无全局控制与形态先验的自我组织。该系统可协调旋转并形成局部凸起(称为叶瓣),由电机细胞簇构成。研究揭示两种独特行为:1)叶瓣间的内凹区域旋转速度高于外侧峰顶,与刚体运动相反;2)细胞旋转方向与整体形态相反。实验表明,尽管机器人形态不影响其相对于自身细胞的角速度,但更大叶瓣会增强细胞旋转,减弱整体形态相对于环境的旋转。即使在多达三分之一致动器失效及显著形变下,仍能维持旋转能力,凸显去中心化、生物启发策略在构建鲁棒与自适应机器人系统中的潜力。

原文摘要 · Abstract (English)

Unlike most human-engineered systems, many biological systems rely on emergent behaviors from low-level interactions, enabling greater diversity and superior adaptation to complex, dynamic environments. This study explores emergent decentralized rotation in the Loopy multicellular robot, composed of homogeneous, physically linked, 1-degree-of-freedom cells. Inspired by biological systems like sunflowers, Loopy uses simple local interactions-diffusion, reaction, and active transport of simulated chemicals, called morphogens-without centralized control or knowledge of its global morphology. Through these interactions, the robot self-organizes to achieve coordinated rotational motion and forms lobes-local protrusions created by clusters of motor cells. This study investigates how these interactions drive Loopy's rotation, the impact of its morphology, and its resilience to actuator failures. Our findings reveal two distinct behaviors: 1) inner valleys between lobes rotate faster than the outer peaks, contrasting with rigid body dynamics, and 2) cells rotate in the opposite direction of the overall morphology. The experiments show that while Loopy's morphology does not affect its angular velocity relative to its cells, larger lobes increase cellular rotation and decrease morphology rotation relative to the environment. Even with up to one-third of its actuators disabled and significant morphological changes, Loopy maintains its rotational abilities, highlighting the potential of decentralized, bio-inspired strategies for resilient and adaptable robotic systems.

多机器人自组织生物启发鲁棒性

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