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About

Anthony Mandow is a prominent robotics researcher whose work spans mobile robot kinematics, motion control, autonomous navigation, and educational robotics. Based at the University of Málaga, Spain, his most influential contributions address the fundamental challenge of accurate motion estimation for robots that slip and skid during operation. His groundbreaking papers on kinematic modeling of tracked and wheeled skid-steer mobile robots — garnering 228 and 182 citations respectively — introduced practical, experimentally validated approaches that bypass complex dynamic computations while still accounting for slippage effects, making real-time control and dead-reckoning significantly more reliable. His early work on the AURORA autonomous greenhouse robot (127 citations) demonstrated his longstanding commitment to applying robotics to real-world agricultural challenges. Mandow has also made notable contributions to path tracking, laser-based motion estimation, articulated vehicle control, and power consumption modeling for tracked robots. His reach extends into robotics education, with a widely adopted framework using LEGO NXT and LabVIEW for undergraduate mechatronics courses (126 citations). More recently, he has explored deep learning-based object detection for search and rescue using thermal and visible-light imagery, reflecting his continued evolution as a researcher addressing cutting-edge autonomous systems challenges.