Date of Thesis
legged locomotion, control, optimization-inspired, heuristic, evolutionary algorithm, machine learning
Investigation uses simulation to explore the inherent tradeoffs ofcontrolling high-speed and highly robust walking robots while minimizing energy consumption. Using a novel controller which optimizes robustness, energy economy, and speed of a simulated robot on rough terrain, the user can adjust their priorities between these three outcome measures and systematically generate a performance curveassessing the tradeoffs associated with these metrics.
Hubicki, Christian, "Energy-Economical Heuristically Based Control of Compass Gait Walking on Stochastically Varying Terrain" (2011). Master’s Theses. 26.