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基于松耦合组件统计力学的粒子机器人。

Particle robotics based on statistical mechanics of loosely coupled components.

机构信息

Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.

Creative Machines Laboratory, Mechanical Engineering Department, Columbia University, New York, NY, USA.

出版信息

Nature. 2019 Mar;567(7748):361-365. doi: 10.1038/s41586-019-1022-9. Epub 2019 Mar 20.

DOI:10.1038/s41586-019-1022-9
PMID:30894722
Abstract

Biological organisms achieve robust high-level behaviours by combining and coordinating stochastic low-level components. By contrast, most current robotic systems comprise either monolithic mechanisms or modular units with coordinated motions. Such robots require explicit control of individual components to perform specific functions, and the failure of one component typically renders the entire robot inoperable. Here we demonstrate a robotic system whose overall behaviour can be successfully controlled by exploiting statistical mechanics phenomena. We achieve this by incorporating many loosely coupled 'particles', which are incapable of independent locomotion and do not possess individual identity or addressable position. In the proposed system, each particle is permitted to perform only uniform volumetric oscillations that are phase-modulated by a global signal. Despite the stochastic motion of the robot and lack of direct control of its individual components, we demonstrate physical robots composed of up to two dozen particles and simulated robots with up to 100,000 particles capable of robust locomotion, object transport and phototaxis (movement towards a light stimulus). Locomotion is maintained even when 20 per cent of the particles malfunction. These findings indicate that stochastic systems may offer an alternative approach to more complex and exacting robots via large-scale robust amorphous robotic systems that exhibit deterministic behaviour.

摘要

生物有机体通过组合和协调随机的低水平组件来实现强大的高级行为。相比之下,大多数当前的机器人系统要么由单一机制组成,要么由协调运动的模块化单元组成。这些机器人需要对单个组件进行明确的控制,以执行特定的功能,并且一个组件的故障通常会使整个机器人无法运行。在这里,我们展示了一个机器人系统,通过利用统计力学现象,可以成功地控制其整体行为。我们通过结合许多松散耦合的“粒子”来实现这一点,这些粒子无法独立运动,也没有单独的身份或可寻址的位置。在提出的系统中,每个粒子仅被允许执行全局信号相位调制的均匀体积振荡。尽管机器人的运动是随机的,并且无法直接控制其单个组件,但我们展示了由多达二十几个粒子组成的物理机器人和具有多达 100000 个粒子的模拟机器人,它们能够进行稳健的运动、物体运输和趋光性(向光刺激移动)。即使有 20%的粒子发生故障,运动也能维持。这些发现表明,随机系统可以通过表现出确定性行为的大规模稳健非晶机器人系统,为更复杂和严格的机器人提供一种替代方法。

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