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FARMS:动物与机器人建模及仿真框架

FARMS: Framework for Animal and Robot Modeling and Simulation.

作者信息

Arreguit Jonathan, Tata Ramalingasetty Shravan, Ijspeert Auke

机构信息

BioRob, School of Engineering, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.

Innobridge Services Sàrl, Lausanne Switzerland.

出版信息

bioRxiv. 2025 Feb 21:2023.09.25.559130. doi: 10.1101/2023.09.25.559130.

Abstract

The study of animal locomotion and neuromechanical control offers valuable insights for advancing research in neuroscience, biomechanics, and robotics. We have developed FARMS (Framework for Animal and Robot Modeling and Simulation), an open-source, interdisciplinary framework, designed to facilitate access to modeling, simulation, and analysis of animal locomotion and bio-inspired robotic systems. By providing an accessible and user-friendly platform, FARMS aims to lower the barriers for researchers to explore the complex interactions between the nervous system, musculoskeletal structures, and their environment. Integrating the MuJoCo physics engine in a modular manner, FARMS enables realistic simulations and fosters collaboration among neuroscientists, biologists, and roboticists. FARMS has already been extensively used to study locomotion in animals such as mice, drosophila, fish, salamanders, and centipedes, serving as a platform to investigate the role of central pattern generators and sensory feedback. This article provides an overview of the FARMS framework, discusses its interdisciplinary approach, showcases its versatility through specific case studies, and highlights its effectiveness in advancing our understanding of locomotion. Overall, the goal of FARMS is to contribute to a deeper understanding of animal locomotion, the development of innovative bio-inspired robotic systems, and promote accessibility in neuromechanical research.

摘要

对动物运动和神经力学控制的研究为推进神经科学、生物力学和机器人技术的研究提供了宝贵的见解。我们开发了FARMS(动物与机器人建模与仿真框架),这是一个开源的跨学科框架,旨在促进对动物运动和受生物启发的机器人系统的建模、仿真及分析。通过提供一个易于访问且用户友好的平台,FARMS旨在降低研究人员探索神经系统、肌肉骨骼结构及其环境之间复杂相互作用的障碍。FARMS以模块化方式集成了MuJoCo物理引擎,能够进行逼真的模拟,并促进神经科学家、生物学家和机器人专家之间的合作。FARMS已经被广泛用于研究小鼠、果蝇、鱼类、蝾螈和蜈蚣等动物的运动,作为研究中枢模式发生器和感觉反馈作用的平台。本文概述了FARMS框架,讨论了其跨学科方法,通过具体案例研究展示了其多功能性,并强调了其在推进我们对运动理解方面的有效性。总体而言,FARMS的目标是有助于更深入地理解动物运动,开发创新的受生物启发的机器人系统,并促进神经力学研究的可及性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/584d/11867414/a27d9aac2a13/nihpp-2023.09.25.559130v3-f0015.jpg

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