Date of Thesis

2011

Thesis Type

Masters Thesis

Department

Mechanical Engineering

First Advisor

Keith Buffinton

Keywords

legged locomotion, control, optimization-inspired, heuristic, evolutionary algorithm, machine learning

Abstract

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.

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