Soaring behaviors in UAVs: ’animat ’ design methodology and current results

Abstract

Saving energy is a critical issue for mini and micro-UAVs. We used tools rooted in the ’animat ’ approach to generate energy saving behaviors for a glider robot. The connection weights of feed-forward neural networks were optimized by evolutionary algorithms to exhibit “soaring ” behaviors, i.e. behaviors that capitalize on aerological conditions to extract energy from the environment, focusing on thermal and slope wind exploitation. Thermal soaring with spiral trajectories and slope soaring with eight-shaped trajectories were thus exhibited. The optimization criterion used for thermal soaring was the average altitude gain. For slope soaring, an additional criterion forced the glider to remain in a limited area. These criteria were high-level specifications of the desired behaviors and did not include any direct description of the strategy needed to get them. I.