Miles Johnson
Papers
1
Total Citations
70
H-Index
1
About
Miles Johnson is a leading researcher in computational robotics and human motion analysis, with a primary focus on inverse optimal control and its applications to biomechanics. His seminal 2012 paper, "A convex approach to inverse optimal control and its application to modeling human locomotion" (70 citations), introduced a groundbreaking framework for inferring the underlying cost functions that drive observed human movement. By reformulating the traditionally non-convex inverse optimal control problem into a convex optimization, Johnson enabled more reliable and computationally efficient modeling of complex locomotion patterns. This work has had a profound impact on fields ranging from rehabilitation robotics to autonomous systems, providing a principled method for understanding how humans make movement decisions. Johnson's contributions have been widely recognized, with his research bridging the gap between control theory and practical human-robot interaction. His innovative approach continues to inspire new methods in learning from demonstration and personalized assistive technologies, making him a key figure in advancing how machines interpret and replicate human motion.
Research Focus
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Top Papers
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