Invariant Extended Kalman Filter for Autonomous Surface Vessels with Partial Orientation Measurements

TL;DR

This paper introduces an Invariant Extended Kalman Filter (InEKF) that effectively integrates partial orientation data from horizon-based sensors and GPS for improved autonomous surface vessel state estimation in open ocean conditions.

Contribution

It develops a novel InEKF framework capable of incorporating partial orientation measurements, specifically roll and pitch from horizon-based sensors, for planar vehicle motion.

Findings

Enhanced state estimation accuracy with partial orientation data

Robustness of the proposed method in open ocean environments

Improved performance over traditional full-orientation EKF methods

Abstract

Autonomous surface vessels (ASVs) are increasingly vital for marine science, offering robust platforms for underwater mapping and inspection. Accurate state estimation, particularly of vehicle pose, is paramount for precise seafloor mapping, as even small surface deviations can have significant consequences when sensing the seafloor below. To address this challenge, we propose an Invariant Extended Kalman Filter (InEKF) framework designed to integrate partial orientation measurements. While conventional estimation often relies on relative position measurements to fixed landmarks, open ocean ASVs primarily observe a receding horizon. We leverage forward-facing monocular cameras to estimate roll and pitch with respect to this horizon, which provides yaw-ambiguous partial orientation information. To effectively utilize these measurements within the InEKF, we introduce a novel framework for incorporating such partial orientation data. This approach contrasts with traditional InEKF implementations that assume full orientation measurements and is particularly relevant for planar vehicle motion constrained to a "seafaring plane." This paper details the developed InEKF framework; its integration with horizon-based roll/pitch observations and dual-antenna GPS heading measurements for ASV state estimation; and provides a comparative analysis against the InEKF using full orientation and a Multiplicative EKF (MEKF). Our results demonstrate the efficacy and robustness of the proposed partial orientation measurements for accurate ASV state estimation in open ocean environments.