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MR-NMPC enables quadrupedal robots to achieve robust bipedal locomotion with wall support, outperforming conventional methods by 2.9 times in challenging environments.
Decentralized MPC with control barrier functions lets multi-robot quadrupeds safely navigate complex environments in real-time, achieving performance on par with centralized approaches but with significantly reduced computation.
Quadrupedal robots can now robustly carry payloads exceeding their own mass on rough terrain, thanks to a novel adaptive MPC framework that learns the payload online.
