A strategy and evaluation method for ground global path planning based on aerial images

Abstract

Autonomous robot navigation consists of establishing a sequence of actions that guarantee safe and efficient locomotion for a robotic system. This work focuses on outdoor ground robot navigation guided by aerial images. We propose a pipeline of image processing, traversability estimation, terrain representation and route planning capable of assessing whether a desired target location is reachable or not. We also propose a dataset and an evaluation method to quantify the average quality of generated paths and measure how well a planning strategy finds possible routes and rejects impossible ones. This evaluation was applied to identify a parameter combination that maximized path feasibility recognition and average path quality. Our results show that the proposed strategy identifies the correct action in 85.8% of the test cases and takes an average of 2.3 s for mapping and 100 ms for path planning over 300 × 300 m2 areas in images of size 1000 × 1000 pixels. We successfully employed our proposed method in a small scale experiment to guide our Hydra v3 mini rover.