Nobuyuki Ueki

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About

Nobuyuki Ueki is a robotics researcher whose work bridges bio-inspired control and nonlinear mechanical systems. His most influential contribution is an obstacle avoidance method for two-wheeled mobile robots, published in 2007 and cited 41 times. In this paper, Ueki adapted the lobula giant movement detector (LGMD)—a neuron in the locust brain that detects approaching predators—to enable robots to sense and evade obstacles in real time. This bio-inspired approach offers a computationally efficient alternative to traditional sensor-based navigation. Ueki also made notable advances in underactuated robotics. His 2004 work on swing-up control of an Acrobot, cited 13 times, models the robot as a horizontal bar gymnast and proposes a nonlinear control scheme that handles the limited joint-angle range of the two-link system. This work contributes to the broader challenge of controlling acrobatic robots with fewer actuators than degrees of freedom. Additionally, Ueki has explored adaptive vibration control for flexible structures subject to unknown disturbances. Though less cited, this research addresses practical challenges in structural and aerospace engineering. Together, Ueki’s work demonstrates a consistent interest in extracting principles from biology and mechanics to solve real-world control problems.