Realizing Robotic Swimming with Unified Fluid-Robot Multiphysics
This work addresses the challenge of simulating and optimizing swimming robots with complex fluid interactions, providing a unified differentiable approach that enables gradient-based optimization and sim-to-real transfer for underwater robotics.
The authors developed a differentiable simulation framework for strongly coupled fluid-robot multiphysics, enabling optimization of swimming gaits for a bioinspired eel robot. They demonstrated successful sim-to-real transfer of undulating swimming and a C-start escape maneuver on physical hardware.
Matching the swimming efficiency and agility of fish has remained an elusive goal in underwater robotics. Such locomotion capabilities rely on complex vortex interactions between the robot's body and the surrounding fluid. However, simulating these dynamics, which are governed by coupled ordinary and partial differential equations, is significantly more difficult than the multi-body dynamics of classical rigid robotic systems. We present a differentiable framework for simulating strongly coupled fluid-robot multiphysics as a unified optimization problem. The coupled manipulator and incompressible Navier-Stokes equations are derived together from a single Lagrangian using the principle of least action. We employ discrete variational mechanics to derive a stable, well-conditioned, and physically accurate scheme for jointly simulating articulated bodies and the surrounding fluid. We leverage the implicit function theorem to compute derivatives of the fully coupled dynamics. Using this simulator and its gradients, we realize undulating swimming gaits and optimize a highly dynamic C-start escape maneuver for a bioinspired eel robot. We validate both gaits on physical hardware, demonstrating successful sim-to-real transfer. Simulation code, hardware data, and schematics for the eel robot can be found here: https://unified-fluid-robot-multiphysics.github.io/