Simulation Model of Obstacle Detection and Mapping System for AUVs

,; Kot, Rafał; Piskur, Paweł; Sigiel, Norbert

doi:10.14313/par_250/19

PAR

2023

DOI: 10.14313/par_250/19

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Simulation Model of Obstacle Detection and Mapping System for AUVs

Rafał Kot,

Paweł Piskur,

Norbert Sigiel

Abstract: This article presents a real-time model of an obstacle detection and environmental mapping system based on image processing for an autonomous underwater vehicle (AUV). The model was based on Tritech Micron Sonar operating parameters with mechanical beam adjustment. The operation of the detection system was verified using a mathematical model of an autonomous underwater vehicle moving in the underwater environment, expressed by a test map prepared based on actual measurements of the above-mentioned sonar. The s… Show more

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2024

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Cited by 2 publications

References 12 publications

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A Comparative Study of Different Collision Avoidance Systems With Local Path Planning for Autonomous Underwater Vehicles

Kot,

Szymak,

Piskur

et al. 2024

IEEE Access

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This article presents an extensive comparison of collision avoidance systems with local path planning based on a mathematical model of an autonomous underwater vehicle (AUV) controlled by the trajectory tracking control system. In the study, six methods such as improved artificial potential field (APF), D* algorithm, dynamic course adjustment (DCA), genetic algorithm (GA), particle swarm optimization (PSO) and rapidly-exploring random tree (RRT) were tested, the efficiency of which was verified on 10 test maps with various types of obstacles' configurations and shapes with taking into account real-time decision-making ability. Both obstacle detection system and collision avoidance systems were extensively fine-tuned to achieve a compromise between collision avoidance efficiency and minimization of computation time. Based on the prepared simulation framework and environment, the trajectory completion percentage, average trajectory deviation, trajectory energy consumption, computation time and percentage of collision trials were assessed. The best results in terms of AUV safety were achieved by the D* and DCA methods. Slightly worse results were obtained by GA and PSO. Considering real-time decision-making ability, the best results were obtained by DCA and APF methods. Based on a detailed analysis of the results, it can be concluded that the DCA method can be used in quick-react emergency systems, and D*, GA and PSO methods are reasonable to use in medium-range local collision avoidance systems.

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A Comparative Study of Different Collision Avoidance Systems With Local Path Planning for Autonomous Underwater Vehicles

Kot,

Szymak,

Piskur

et al. 2024

IEEE Access

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Fuzzy Inference-Based Adaptive Sonar Control for Collision Avoidance in Autonomous Underwater Vehicles

Kot

2024

Polish Maritime Research

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This article discusses the use of adaptive control in the sonar scanning sector within an obstacle detection system, to improve the effectiveness of collision avoidance for autonomous underwater vehicles (AUVs). An adaptive network-based fuzzy inference system (ANFIS) was used for dynamic calculations of the sonar scanning sector. Based on 100 simulation scenarios containing various trajectories created by the mission planner, with various shapes, dimensions and arrangements of static obstacles, and various arrangements and displacement vectors of dynamic obstacles, the effectiveness of the proposed system was tested in comparison with other classical approaches such as a single echosounder and sonar with a fixed scanning sector width. The above sensor configurations were evaluated in terms of the percentage of collision-free trials, the average percentage of trajectory completion, and the average number of activations of the collision avoidance system. Simulations conducted based on the mathematical model of the AUV confirmed that the proposed approach increased the effectiveness of collision avoidance systems for AUVs compared to classical echosounder and sonar-based systems.

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Simulation Model of Obstacle Detection and Mapping System for AUVs

Cited by 2 publications

References 12 publications

A Comparative Study of Different Collision Avoidance Systems With Local Path Planning for Autonomous Underwater Vehicles

A Comparative Study of Different Collision Avoidance Systems With Local Path Planning for Autonomous Underwater Vehicles

Fuzzy Inference-Based Adaptive Sonar Control for Collision Avoidance in Autonomous Underwater Vehicles

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