A novel versatile architecture for autonomous underwater vehicle’s motion planning and task assignment

Abstract

Expansion of today's underwater scenarios and missions necessitates the requestion for robust decision making of the Autonomous Underwater Vehicle (AUV); hence, design an efficient decision making framework is essential for maximizing the mission productivity in a restricted time. This paper focuses on developing a deliberative conflict-free-task assignment architecture encompassing a Global Route Planner (GRP) and a Local Path Planner (LPP) to provide consistent motion planning encountering both environmental dynamic changes and a priori knowledge of the terrain, so that the AUV is reactively guided to the target of interest in the context of an uncertain underwater environment. The architecture involves three main modules: The GRP module at the top level deals with the task priority assignment, mission time management, and determination of a feasible route between start and destination point in a large scale environment. The LPP module at the lower level deals with safety considerations and generates collision-free optimal trajectory between each specific pair of waypoints listed in obtained global route. Re-planning module tends to promote robustness and reactive ability of the AUV with respect to the environmental changes. The experimental results for different simulated missions, demonstrate the inherent robustness and drastic efficiency of the proposed scheme in enhancement of the vehicles autonomy in terms of mission productivity, mission time management, and vehicle safety.

Current advancements on autonomous mission planning and management systems: An AUV and UAV perspective

“…The system incorporates two deliberative and reactive execution layers to satisfy autonomy requirements in both mission scheduling and motion planning for generating prompt actions/reactions. Hybrid Synchronous Mission and Motion Planning System [74] [75] [76] These studies provided vehicle's decision autonomy through designing a hybrid synchronous system for ordering the execution of the tasks and guiding the AUV toward the target of interest in the higher layer; and using a SA-based motion planner as an action generator to ensure a safe and efficient deployment. They mostly focused on managing mission time and increasing mission productivity, while the effect of water current force as an important concern for AUV's deployment is not addressed.…”

A Comprehensive Review of Path Planning Algorithms for Autonomous Underwater Vehicles

“…Wu et al [138] applied the GA subjected to non-linear constraints to generate cost effective, safe paths for a team of AUVs relying on the knowledge of the waypoints and obstacles. The algorithm is segregated in three modules.…”

“…•Improves stability, robustness and performance of the system •Low computation cost •Each block is designed to be passive Predictable Evolutionary algorithms [136][137][138] Time optimal Achieved Low…”

Online path planning for AUV rendezvous in dynamic cluttered undersea environment using evolutionary algorithms

“…The AUV is equipped with sonar sensors for measuring the velocity and coordinates of the objects with a level of uncertainty depicted with a normal distribution. Modelling of different obstacles derived from [34][35][36] are formulated as follows: 1) Quasi-static Uncertain Objects: Object's position should be placed between the location of AUV's starting and destination spot in the given map. This group of objects are introduced with a fixed-center generated at commencement and an uncertain radius that varying over time according to Eq.…”