P. J. McKerrow

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About

P. J. McKerrow’s research lies at the intersection of mobile robotics, sensor perception, and intelligent data interpretation, with a particular focus on ultrasonic sensing. His work has fundamentally advanced how robots perceive and navigate complex environments by tackling the challenge of multiple reflection paths—a common source of error in ultrasonic range readings. In his highly cited 2002 paper, McKerrow developed a geometric model to predict and correct for these reflections, dramatically improving the accuracy of distance measurements. He further extended this work by integrating data fusion techniques, enabling robots to reason beyond raw sensor limitations and build more reliable environmental models. His contributions to odometry calibration for four-wheeled robots, detailed in a 2003 study, provided practical methods for precise steering angle and movement measurement, directly impacting real-world robot deployment. Notably, McKerrow pioneered the use of Continuous Transmitted Frequency Modulated (CTFM) ultrasonic sensors for landmark recognition, demonstrating with a neural network that plants could be reliably identified—a novel application with implications for agricultural robotics. With over 58 citations across his key papers, McKerrow’s work remains essential for researchers developing robust, perception-driven autonomous systems.