Paper Info
Title
Optimal route planning with prioritized task scheduling for AUV missions
Abstract
This paper presents a solution to Autonomous Underwater Vehicles (AUVs) large scale route planning and task assignment joint problem. Given a set of constraints (e.g., time) and a set of task priority values, the goal is to find the optimal route for underwater mission that maximizes the sum of the priorities and minimizes the total risk percentage while meeting the given constraints. Making use of the heuristic nature of genetic and swarm intelligence algorithms in solving NP-hard graph problems, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are employed to find the optimum solution, where each individual in the population is a candidate solution (route). To evaluate the robustness of the proposed methods, the performance of the all PS and GA algorithms are examined and compared for a number of Monte Carlo runs. Simulation results suggest that the routes generated by both algorithms are feasible and reliable enough, and applicable for underwater motion planning. However, the GA-based route planner produces superior results comparing to the results obtained from the PSO based route planner.
Year
DOI
Venue
2016
10.1109/IRIS.2015.7451578
2015 IEEE International Symposium on Robotics and Intelligent Sensors (IRIS)
Keywords
Field
DocType
autonomous underwater vehicle,route planning,particle swarm optimization,genetic algorithm
Motion planning,Particle swarm optimization,Population,Mathematical optimization,Heuristic,Simulation,Computer science,Swarm intelligence,Multi-swarm optimization,Robustness (computer science),Genetic algorithm
Journal
Volume
ISSN
Citations 
abs/1604.03303
IEEE International Symposium on Robotics and Intelligent Sensors, pp 7-15, 2015
1
PageRank 
References 
Authors
0.42
9
5
Name
Order
Citations
PageRank
Somaiyeh Mahmoud Zadeh1151.76
David M. W. Powers250067.39
Karl Sammut36610.85
Andrew Lammas4222.91
Amir Mehdi Yazdani5507.48