FARMS: Framework for Animal and Robot Modeling and Simulation

Abstract

The apparent ease with which animals move hides the complexity of the neuromechanical systems underlying locomotion. This behavior remains difficult to understand and replicate, motivating sustained interest across biology, neuroscience, robotics, and computer animation. Despite extensive progress, existing approaches often focus on isolated aspects of locomotion, limiting the integration of neural control, biomechanics, and environmental interactions within a unified modeling framework. Bridging biological insight, robotic implementation, and physically based character animation therefore requires shared, extensible computational tools that promote reuse, while supporting physically grounded modeling and control across animals and robots. Our key technical contribution is the development of FARMS (Framework for Animal and Robot Modeling and Simulation), an open-source, interdisciplinary Python framework that integrates and extends existing open-source software for 3D modeling, experiment design, optimization, and data analysis within a modular and extensible workflow. FARMS lowers the barrier for constructing and simulating whole-body animal and robot models, enabling the definition of skeletal structures, musculature, and neural circuits at multiple levels of abstraction within a unified workflow. FARMS has already been used to model and study locomotor behaviors in a variety of animals and robots, and we demonstrate the frameworks versatility and effectiveness through a series of simulation case studies. We show that FARMS enables the reuse of model components across morphologies of different complexities, while capturing mechanical interactions between the body and diverse environments, including terrestrial and aquatic settings. This allows the study and synthesis of walking, swimming, and locomotor transitions within a single, unified framework.