Carl Bou Mansour

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About

Carl Bou Mansour is a pioneering researcher at the intersection of bio-inspired robotics and sensory ecology, with a primary focus on bat echolocation and obstacle avoidance. His major contributions lie in developing robotic models that replicate the sonar-based navigation strategies of echolocating bats, particularly in complex, cluttered environments. In his most-cited work, "Avoidance of non-localizable obstacles in echolocating bats: A robotic model" (2019, 18 citations), Bou Mansour demonstrated how bats overcome the challenge of overlapping echoes from dense vegetation—a problem where limited temporal and spatial resolution prevents separate perception of individual objects. By building physical robotic platforms, he showed that bats rely on acoustic gaze scanning to infer 3D positions and avoid obstacles, even when echoes are non-localizable. His follow-up study (2019, 2 citations) further quantified the benefits of this scanning behavior. Bou Mansour’s work bridges neuroethology and engineering, offering insights for autonomous navigation systems. His robotic models have become a benchmark for understanding how biological sonar operates in real-world complexity, making him a key figure in biomimetic robotics and sensory biology.