@article {69290, title = {Whole-body simulation of realistic fruit fly locomotion with deep reinforcement learning}, journal = {Nature}, year = {2025}, month = {2025 Apr 23}, abstract = {

The body of an animal influences how its nervous system generates behavior1. Accurately modeling the neural control of sensorimotor behavior 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 behaviors, including both terrestrial and aerial locomotion. We validate its versatility by replicating realistic walking and flight behaviors. To support these behaviors, we develop new 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. Additionally, we show the use of visual sensors and hierarchical motor control, training a high-level controller to reuse a pre-trained 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 behavior in an embodied context.

Preprint:\ www.biorxiv.org/content/early/2024/03/14/2024.03.11.584515

}, doi = {10.1038/s41586-025-09029-4}, url = {https://doi.org/10.1038/s41586-025-09029-4}, author = {Roman Vaxenburg and Igor Siwanowicz and Josh Merel and Alice A Robie and Carmen Morrow and Guido Novati and Zinovia Stefanidi and Gwyneth M Card and Michael B Reiser and Matthew M Botvinick and Kristin M Branson and Yuval Tassa and Srinivas C Turaga} }