Towards distributed coverage of complex spatiotemporal profiles
John Oluwagbemiga Oyekan, Huosheng Hu · 2011
Inspired by self-organization in natural organisms, an approach that would enable robotic agents form a visual representation of an invisible distributed hazardous substance is presented. Such a resource would enable humans observe and stay away from areas of high hazardous substance concentration. In this work, a proportional-integral control law and a machine learning scheme is used to obtain optimal parameter values that would enable optimal visual mapping whilst keeping computational resources low.