Physical Consistent Path Planning for Unmanned Surface Vehicles under Complex Marine Environment

Abstract

The increasing demand for safe and efficient maritime transportation has underscored the necessity of developing effective path-planning algorithms for Unmanned Surface Vehicles (USVs). However, the inherent complexities of the ocean environment and the non-holonomic properties of the physical system have posed significant challenges to designing feasible paths for USVs. To address these issues, a novel path planning framework is elaborately designed, which consists of an optimization model, a meta-heuristic solver, and a Clothoid-based path connector. First, by encapsulating the intricate nature of the ocean environment and ship dynamics, a multi-objective path planning problem is designed, providing a comprehensive and in-depth portrayal of the underlying mechanism. By integrating the principles of the candidate set random testing initialization and adaptive probability set, an enhanced genetic algorithm is devised to fully exploit the underlying optimization problem in constrained space, contributing to the global searching ability. Accounting for the non-holonomic constraints, the fast-discrete Clothoid curve is capable of maintaining and improving the continuity of the path curve, thereby promoting strong coordination between the planning and control modules. A thorough series of simulations and comparisons conducted in diverse ocean scenarios has conclusively demonstrated the effectiveness and superiority of the proposed path planning framework.

Route Planning Algorithms for Unmanned Surface Vehicles (USVs): A Comprehensive Analysis

“…Improved crossover and variation operators, superior coding methods, and fine-tuned genetic parameters have been the focus of efforts to improve GA. In [73], by combining the concepts of initiating candidate sets through random testing and utilizing an adaptive probability set, an improved genetic algorithm is created to effectively address optimization problems within confined spaces. This approach enhances the algorithm's capability for global exploration.…”

A Novel Unmanned Surface Vehicle Path-Planning Algorithm Based on A* and Artificial Potential Field in Ocean Currents

“…Despite a lot of research aimed at properly tackling ocean currents' impacts on USV paths, there remains a study gap regarding USV path planning under varying current conditions [59]. We can explore path planning in a current environment in terms of the interaction that exists between USVs and currents.…”