Field Testing of a Stochastic Planner for ASV Navigation Using Satellite Images

TL;DR

This paper presents a stochastic planning system for autonomous surface vessels that uses satellite imagery and local sensors to navigate water bodies with uncertain traversability, validated through real-world lake experiments.

Contribution

It introduces a novel multi-sensor navigation framework that models traversability uncertainties as stochastic edges and optimizes mission policies for ASV water-quality monitoring.

Findings

Successfully navigated 3 km lake missions using satellite, GPS, vision, and sonar sensors.

Effectively disambiguated traversability of uncertain paths in real-time.

Provided practical insights and future directions for reliable ASV navigation.

Abstract

We introduce a multi-sensor navigation system for autonomous surface vessels (ASV) intended for water-quality monitoring in freshwater lakes. Our mission planner uses satellite imagery as a prior map, formulating offline a mission-level policy for global navigation of the ASV and enabling autonomous online execution via local perception and local planning modules. A significant challenge is posed by the inconsistencies in traversability estimation between satellite images and real lakes, due to environmental effects such as wind, aquatic vegetation, shallow waters, and fluctuating water levels. Hence, we specifically modelled these traversability uncertainties as stochastic edges in a graph and optimized for a mission-level policy that minimizes the expected total travel distance. To execute the policy, we propose a modern local planner architecture that processes sensor inputs and plans paths to execute the high-level policy under uncertain traversability conditions. Our system was tested on three km-scale missions on a Northern Ontario lake, demonstrating that our GPS-, vision-, and sonar-enabled ASV system can effectively execute the mission-level policy and disambiguate the traversability of stochastic edges. Finally, we provide insights gained from practical field experience and offer several future directions to enhance the overall reliability of ASV navigation systems.