RUBI is controlled using reinforcement learning and is capable of stable walking on a variety of ground environments, including flat ground, slopes, gravel, and slippery snow.
Development and Reinforcement Learning based Control of RUBI
RUBI at the Humanoid 2025
To expand the robot's operation to water-exposed environments, experiments were conducted under both spray and submersion conditions. These tests verified the robot's waterproof design performance and the stability and robustness of the control algorithm.
Walking of RUBI in Spray and Underwater Environments
RUBI's point-foot structure makes it structurally disadvantageous for stable self-sufficiency while stationary. Nevertheless, we implemented an algorithm that learns stand-up motion through reinforcement learning and enables the transition to walking after independence.
RUBI, Stand Up!
coming soon ...
JeongHwan Jang
JaeHyeok Song