Papers
4
Total Citations
27
H-Index
3
About
Michael C. Mulder is a robotics and control systems researcher whose work has focused primarily on intelligent motion control for multi-jointed robotic arms and bipedal locomotion. His most significant contributions center on the development of biomimetic control algorithms that draw inspiration from human movement to solve complex robotic coordination challenges. Mulder's most influential work, published in 2002 and accumulating 11 citations, introduced a minimum-effort control algorithm for cooperating sensor-driven robotic arms — a system that generates multiple humanlike arm movement strategies and selects the optimal approach based on minimizing expended effort. This biologically inspired framework also demonstrated an inherent capability for obstacle avoidance, setting it apart from conventional approaches. A follow-up study in 2003 (8 citations) further examined the algorithm's behavior in obstacle-rich environments, while a companion paper from 2002 (6 citations) validated the underlying sensor-driven control model using an anthropomorphic framework, reasoning by analogy from human joint mechanics to develop robust robotic solutions. Earlier in his career, Mulder explored dynamic stability in bipedal motion (1990), demonstrating a longstanding interest in adaptive, human-centered control strategies. His body of work reflects a consistent commitment to bridging biological movement principles with practical robotic applications.
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