Completeness Seeking Probabilistic Coverage Estimation using Uncertain State Estimates

Abstract

This paper develops a coverage-centric adaptive path planner to visually survey a planar environment. This is achieved by modifying an existing path planning architecture to use a novel coverage estimation approach called convolved coverage estimation (CCE). The planner maximizes the probability of terrain coverage and exploits terrain features for loop closure to keep path uncertainty in check. The developed algorithm considers multi-dimensional uncertainty, operates in real-time, and does not require external correction methods like GPS. These characteristics are validated in high-fidelity simulation and flight tests on an unmanned aerial vehicle (UAV).