AUTO-IceNav: A Local Navigation Strategy for Autonomous Surface Ships in Broken Ice Fields

TL;DR

AUTO-IceNav is a novel autonomous navigation framework for ships in broken ice fields, using receding-horizon planning, a unique collision energy minimization cost, and optimization to ensure safe and efficient Arctic navigation.

Contribution

The paper introduces a new framework combining receding-horizon planning, a collision energy-based cost function, and optimization for autonomous ship navigation in ice fields.

Findings

Validated in simulation and physical tests.

Reduced collision energy and improved navigation safety.

Effective in complex Arctic ice conditions.

Abstract

Ice conditions often require ships to reduce speed and deviate from their main course to avoid damage to the ship. In addition, broken ice fields are becoming the dominant ice conditions encountered in the Arctic, where the effects of collisions with ice are highly dependent on where contact occurs and on the particular features of the ice floes. In this paper, we present AUTO-IceNav, a framework for the autonomous navigation of ships operating in ice floe fields. Trajectories are computed in a receding-horizon manner, where we frequently replan given updated ice field data. During a planning step, we assume a nominal speed that is safe with respect to the current ice conditions, and compute a reference path. We formulate a novel cost function that minimizes the kinetic energy loss of the ship from ship-ice collisions and incorporate this cost as part of our lattice-based path planner. The solution computed by the lattice planning stage is then used as an initial guess in our proposed optimization-based improvement step, producing a locally optimal path. Extensive experiments were conducted both in simulation and in a physical testbed to validate our approach.