Max Robotics — Global Service Robot Directory + US Certification

About

Paul Brunn is a pioneering researcher in industrial robotics, with a career focused on making robot systems more accurate, affordable, and accessible. His primary research areas include robot metrology and calibration, inverse kinematic solutions, collision avoidance, and the application of artificial neural networks (ANNs) to engineering problems. Brunn’s major contributions are twofold: he provided critical market analyses that exposed the prohibitive costs of calibration systems, and he developed innovative, low-cost solutions to overcome these barriers. His most cited work, “Robot metrology and calibration systems ‐ a market review” (17 citations), remains a foundational reference for understanding the commercial landscape of robot calibration. He also advanced the field by using ANNs to solve the challenging inverse kinematic problem for precise path control (15 citations), and by creating a hybrid ANN method to compensate for offset errors in precision machinery. Notably, Brunn demonstrated a practical, cost-effective approach to robotics by rejuvenating obsolete industrial robots—such as the ASEA IRB6—using simple microcontroller-based control boards, proving that advanced automation does not require expensive new hardware. His work continues to influence researchers seeking to democratize robotic technology.