Addressing the Entry Barrier for Experimentation in Perception-aware Trajectory Planning for Planetary Rovers

Abstract

To fully evaluate perception-aware planning methods for planetary rover, we need a platform that takes action commands and captures perception data. Even with suitable hardware and simulation available to us, there exists an "entry barrier" for performing research in active vision, as developing methods with a system-in-the-loop is time intensive. We present our approach for tackling this entry barrier by incrementally moving from toy examples to integration and deployment on real robots. Our approach aims at reducing the overall development complexity by producing intermediate results that are used to validate and evaluate the active algorithm.