Alan C. O'Connor

Papers

Total Citations

H-Index

About

Alan C. O’Connor is a leading figure in robotics and autonomous navigation, with a primary focus on developing elegant, biologically-inspired control strategies for mobile robots. His most influential work, the 2004 paper “Experimental study of curvature-based control laws for obstacle avoidance” (51 citations), introduced a novel curvature-based steering control law that enables unicycle-type robots—including aerial vehicles—to avoid obstacles while traveling at constant speed. This contribution is notable for its practical, experimental validation: O’Connor systematically explored and compared different methods of estimating curvature from noisy range data, bridging the gap between theoretical control theory and real-world sensor limitations. His research has had a lasting impact on the fields of reactive navigation and sensor-based control, providing a robust framework for robots to navigate cluttered environments without complex mapping. By emphasizing simplicity and real-time performance, O’Connor’s work has influenced subsequent generations of obstacle avoidance algorithms, particularly in applications requiring fast, reliable motion planning. His contributions remain essential reading for students and researchers seeking to understand how geometric reasoning can be harnessed for autonomous mobility.