Vaxenburg Roman, Siwanowicz Igor, Merel Josh, Robie Alice A, Morrow Carmen, Novati Guido, Stefanidi Zinovia, Both Gert-Jan, Card Gwyneth M, Reiser Michael B, Botvinick Matthew M, Branson Kristin M, Tassa Yuval, Turaga Srinivas C
HHMI Janelia Research Campus, Ashburn, VA, USA.
Fauna Robotics, New York City, NY, USA.
Nature. 2025 Apr 23. doi: 10.1038/s41586-025-09029-4.
The body of an animal influences how its nervous system generates behaviour. Accurately modelling the neural control of sensorimotor behaviour requires an anatomically detailed biomechanical representation of the body. Here we introduce a whole-body model of the fruit fly Drosophila melanogaster in a physics simulator. Designed as a general-purpose framework, our model enables the simulation of diverse fly behaviours, including both terrestrial and aerial locomotion. We validate its versatility by replicating realistic walking and flight behaviours. To support these behaviours, we develop phenomenological models for fluid and adhesion forces. Using data-driven, end-to-end reinforcement learning, we train neural network controllers capable of generating naturalistic locomotion along complex trajectories in response to high-level steering commands. Furthermore, we show the use of visual sensors and hierarchical motor control, training a high-level controller to reuse a pretrained low-level flight controller to perform visually guided flight tasks. Our model serves as an open-source platform for studying the neural control of sensorimotor behaviour in an embodied context.
动物的身体会影响其神经系统产生行为的方式。要准确模拟感觉运动行为的神经控制，需要对身体进行解剖学上详细的生物力学表征。在此，我们在物理模拟器中引入了果蝇黑腹果蝇的全身模型。作为一个通用框架设计，我们的模型能够模拟果蝇的各种行为，包括陆地和空中运动。我们通过复制逼真的行走和飞行行为来验证其通用性。为了支持这些行为，我们开发了流体和粘附力的现象学模型。使用数据驱动的端到端强化学习，我们训练能够响应高级转向命令沿复杂轨迹生成自然运动的神经网络控制器。此外，我们展示了视觉传感器和分层运动控制的使用，训练一个高级控制器重用预训练的低级飞行控制器来执行视觉引导的飞行任务。我们的模型作为一个开源平台，用于在具体情境中研究感觉运动行为的神经控制。
