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About

Bernhard Hengst is a leading researcher in autonomous mobile robotics, with a focus on legged locomotion, terrain perception, and cognitive architectures. His work has been instrumental in enabling robots to traverse rough, unstructured environments—a critical challenge for search-and-rescue and field robotics. Hengst’s most cited paper, “Omnidirectional Locomotion for Quadruped Robots” (53 citations), established foundational techniques for versatile robot movement. He further advanced the field by developing terrain feature extractors from range images (26 citations) and pioneering behavioural cloning approaches for driving robots over rough terrain (16 citations), allowing controllers to learn from human demonstration rather than relying on complex physical models. Hengst also contributed to bipedal balancing and walking through reinforcement learning (14 citations), and explored the integration of symbolic and sub-symbolic representations for cognitive robotics (5 citations). A key figure in the RoboCup community, he was part of the world champion rUNSWift team in 2003 and has authored multiple papers on legged robot soccer. With over 150 total citations across his work, Hengst’s research continues to shape how robots perceive, navigate, and act in challenging real-world environments.