Boston Dynamics adds wheels to Atlas robot
The Robot Report: Boston Dynamics adds wheels to Atlas humanoid to test whole-body control
Bridging the divide between deterministic physics-based control and policy-driven adaptation, Boston Dynamics has deployed a hybrid locomotion architecture on a wheeled variant of its Atlas humanoid. The “experiment” combined classical model-based motor control with whole-body reinforcement learning to maintain dynamic stability across unstructured, real-world terrain. In the video, Andy Wu, controls engineer for Atlas at Boston Dynamics, highlights some recent experiments that he
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Boston Dynamics attached wheels to its Atlas humanoid robot to conduct control engineering experiments that test how the robot can maintain stability and adapt to real-world terrain. The experiment combined classical physics-based motor control with whole-body reinforcement learning, allowing Atlas to learn wheeled locomotion behaviors in simulation and then execute them in real environments, including performing maneuvers like pirouettes and switching between rolling on flat ground and articulated movement over obstacles. The retrofit required only a simple custom adapter mounting a scooter rim to the robot's existing ankle actuator, demonstrating that the robot's design allowed for easy modification. The primary finding was that merging traditional motor controls with reinforcement learning-based adaptation produces better real-world performance than using either method alone, though Boston Dynamics emphasized this wheeled version is a research testbed rather than a commercial product.
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