Robert Schuller
Papers
8
Total Citations
67
H-Index
4
About
Robert Schuller is a leading researcher in humanoid robotics, specializing in dynamic locomotion and whole-body motion control. His work centers on enabling robots to walk, run, jump, and recover from pushes with unprecedented agility and robustness. Schuller’s major contributions include pioneering the use of the three-dimensional Divergent Component of Motion (3D-DCM) framework for unified gait generation, and developing novel algorithms for online learning of centroidal angular momentum (CAM) to enhance balance and reduce destabilizing contact torques. His 2021 paper on push recovery, which actively generates CAM references based on push force, has garnered 32 citations and is a foundational reference in the field. Schuller has also advanced humanoid capabilities in challenging scenarios, such as agile standing-up from the ground using multi-contact strategies, and has explored limb trajectory optimization for running. His work extends to space robotics, where he optimizes multi-arm robot locomotion to minimize disturbances during in-orbit assembly. With a growing citation impact and a focus on real-world deployment, Schuller is shaping the next generation of agile, resilient humanoid robots for home, industrial, and space environments.
Research Focus
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Top Papers
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