Max Robotics — Global Service Robot Directory + US Certification

About

C.J.B. Macnab is a researcher whose work spans neural network-based adaptive control, robotics, haptics, and biomechanical locomotion. Over more than two decades, Macnab has made sustained contributions to the challenge of achieving stable, intelligent robot control in uncertain and dynamic environments. His most influential work applies cerebellar-model arithmetic computer (CMAC) neural networks and Lyapunov-based stability analysis to adaptive control of flexible and elastic-joint robots, demonstrating that reliable trajectory tracking can be achieved without extensive prior learning or precise system modeling. A recurring theme across his research is preventing instability in adaptive systems — particularly the "bursting" phenomenon — through innovative algorithmic safeguards, reflecting a commitment to practical, safe implementation. Macnab has also contributed meaningfully to surgical robotics, exploring haptic feedback systems and time-delay compensation to enhance teleoperated neurosurgical procedures, work that bridges engineering and clinical practice. His investigations into bipedal locomotion and energy-optimal walking mechanics further demonstrate the breadth of his interests. His most-cited paper on haptics for neurosurgeons (34 citations) underscores his ability to communicate technical advances to interdisciplinary audiences. Collectively, his body of work offers both theoretical rigor and real-world applicability, making it valuable reading for students in control systems, medical robotics, and biomechanics.