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About

Joseph Norby is a leading researcher in legged robotics, specializing in motion planning, control, and dynamic locomotion. His work focuses on enabling robots to perform agile, real-time maneuvers in complex, unstructured environments—a critical challenge for field robotics. Norby’s most impactful contribution is a fast, global motion planning algorithm for dynamic legged robots (2020, 35 citations), which constructs long-horizon plans that incorporate flight phases, overcoming the static-stability limitations of prior methods. He further advanced robot agility by studying aerodynamic drag in lightweight tails (2021, 32 citations), inspired by nature’s efficient designs, allowing robots to regulate orientation during running and leaping without heavy, energy-expensive appendages. His research on proprioception and tail control (2023, 11 citations) demonstrated robust quadruped locomotion over extreme terrain, such as rocky hills and curbs, by handling contact uncertainty. Norby also introduced Adaptive Complexity Model Predictive Control (2024, 9 citations), a formulation that dynamically adjusts model complexity while preserving stability—a breakthrough for real-time control. His work has been published at top robotics venues, earning recognition for pushing the boundaries of dynamic legged locomotion and control theory.