Integrated Motion Planning and Feedback Control Methods

From assistive rehabilitation to autonomous exploration, robotics effectively allows us to more consistently explore smarter and farther. To realize this requires designing agile systems – as efficient and fluid operation implies driving near performance bounds. My research interests are in synthesizing dynamic motion. I look at this from both: (1) an integrated planning and control perspective (i.e., model → action) and (2) a system identification and reduction perspective (i.e., action→ model). Of course, no model is perfect. Abstraction is engineering. The goal is to know where the boundaries lie. Careful model factoring and approximation (using Lie group symmetries and Calculus of Variations) allows systems to leverage the results of large complex models/simulations (that are generally pre-computed off-line) adaptively during on-line operation. This provides near-optimality with speed. This is currently motivated by two applications: motion tracking and optimization for (1) optimizing mineral extraction operations and (2) for trajectories in gymnastics and diving.