scholarly journals Path planning and collision avoidance for autonomous surface vehicles I: a review

2021 ◽  
Author(s):  
Anete Vagale ◽  
Rachid Oucheikh ◽  
Robin T. Bye ◽  
Ottar L. Osen ◽  
Thor I. Fossen
Keyword(s):  
Path Planning ◽  
Collision Avoidance ◽  
Regulatory Framework ◽  
Autonomous Surface Vehicles ◽  
Navigation And Control ◽  
Potential Benefits ◽  
Planning Algorithms ◽  
And Control

AbstractAutonomous surface vehicles are gaining increasing attention worldwide due to the potential benefits of improving safety and efficiency. This has raised the interest in developing methods for path planning that can reduce the risk of collisions, groundings, and stranding accidents at sea, as well as costs and time expenditure. In this paper, we review guidance, and more specifically, path planning algorithms of autonomous surface vehicles and their classification. In particular, we highlight vessel autonomy, regulatory framework, guidance, navigation and control components, advances in the industry, and previous reviews in the field. In addition, we analyse the terminology used in the literature and attempt to clarify ambiguities in commonly used terms related to path planning. Finally, we summarise and discuss our findings and highlight the potential need for new regulations for autonomous surface vehicles.

scholarly journals COLREG-Compliant Optimal Path Planning for Real-Time Guidance and Control of Autonomous Ships

2021 ◽  
Vol 9 (4) ◽  
pp. 405
Author(s):  
Raphael Zaccone
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Collision Avoidance ◽  
Autonomous Navigation ◽  
Optimal Path ◽  
Open Water ◽  
Optimal Path Planning ◽  
Guidance And Control ◽  
Real Time Applications ◽  
And Control

While collisions and groundings still represent the most important source of accidents involving ships, autonomous vessels are a central topic in current research. When dealing with autonomous ships, collision avoidance and compliance with COLREG regulations are major vital points. However, most state-of-the-art literature focuses on offline path optimisation while neglecting many crucial aspects of dealing with real-time applications on vessels. In the framework of the proposed motion-planning, navigation and control architecture, this paper mainly focused on optimal path planning for marine vessels in the perspective of real-time applications. An RRT*-based optimal path-planning algorithm was proposed, and collision avoidance, compliance with COLREG regulations, path feasibility and optimality were discussed in detail. The proposed approach was then implemented and integrated with a guidance and control system. Tests on a high-fidelity simulation platform were carried out to assess the potential benefits brought to autonomous navigation. The tests featured real-time simulation, restricted and open-water navigation and dynamic scenarios with both moving and fixed obstacles.

Overview of Path-Planning and Obstacle Avoidance Algorithms for UAVs: A Comparative Study

2018 ◽  
Vol 06 (02) ◽  
pp. 95-118 ◽  
Author(s):  
Mohammadreza Radmanesh ◽  
Manish Kumar ◽  
Paul H. Guentert ◽  
Mohammad Sarim
Keyword(s):  
Path Planning ◽  
Comparative Study ◽  
Operating Conditions ◽  
Computational Time ◽  
Safe Operation ◽  
Sense And Avoid ◽  
Planning Algorithms ◽  
And Control ◽  
Global And Local ◽  
Further Development

Unmanned aerial vehicles (UAVs) have recently attracted the attention of researchers due to their numerous potential civilian applications. However, current robot navigation technologies need further development for efficient application to various scenarios. One key issue is the “Sense and Avoid” capability, currently of immense interest to researchers. Such a capability is required for safe operation of UAVs in civilian domain. For autonomous decision making and control of UAVs, several path-planning and navigation algorithms have been proposed. This is a challenging task to be carried out in a 3D environment, especially while accounting for sensor noise, uncertainties in operating conditions, and real-time applicability. Heuristic and non-heuristic or exact techniques are the two solution methodologies that categorize path-planning algorithms. The aim of this paper is to carry out a comprehensive and comparative study of existing UAV path-planning algorithms for both methods. Three different obstacle scenarios test the performance of each algorithm. We have compared the computational time and solution optimality, and tested each algorithm with variations in the availability of global and local obstacle information.

AUV path planning, navigation, and control using geophysical data

2019 ◽  
Author(s):  
J. Quintas ◽  
N. Hung ◽  
N. Crasta ◽  
F. Curado-Teixeira ◽  
P. Lima ◽  
...  
Keyword(s):  
Path Planning ◽  
Geophysical Data ◽  
Navigation And Control ◽  
And Control

scholarly journals Guidance scheme for paths without temporary restrictions using the Krick Felix model boat under the influence of sea currents

2018 ◽  
Vol 16 (46) ◽  
pp. 59-70
Author(s):  
Leidys Miranda Jiménez ◽  
Yunier Yunier Valeriano-Medina ◽  
Ángel Camero Álvarez
Keyword(s):  
Control Systems ◽  
Guidance System ◽  
Human Intervention ◽  
Autonomous Surface Vehicles ◽  
Navigation And Control ◽  
Sea Currents ◽  
Guidance Algorithm ◽  
And Control

The autonomous surface vehicles are composed of a guidance, navigation, and control systems where the first one plays an important role in missions without human intervention. This article presents the design of a guidance system made of an I-LOS controller, where its purpose is to achieve the convergence and the precise following of straight paths, regardless of the sea currents presence. The controller gains adjustment is performed according to the vehicle features and the geometry of the path to follow. The proposed guidance algorithm is assessed through simulation, obtaining favorable results.

scholarly journals Path planning and collision avoidance for autonomous surface vehicles II: a comparative study of algorithms

2021 ◽  
Author(s):  
Anete Vagale ◽  
Robin T. Bye ◽  
Rachid Oucheikh ◽  
Ottar L. Osen ◽  
Thor I. Fossen
Keyword(s):  
Path Planning ◽  
Comparative Study ◽  
Collision Avoidance ◽  
State Of The Art ◽  
Potential Fields ◽  
Large Set ◽  
Enabling Technology ◽  
Fast Marching ◽  
Autonomous Surface Vehicles ◽  
Current State

AbstractArtificial intelligence is an enabling technology for autonomous surface vehicles, with methods such as evolutionary algorithms, artificial potential fields, fast marching methods, and many others becoming increasingly popular for solving problems such as path planning and collision avoidance. However, there currently is no unified way to evaluate the performance of different algorithms, for example with regard to safety or risk. This paper is a step in that direction and offers a comparative study of current state-of-the art path planning and collision avoidance algorithms for autonomous surface vehicles. Across 45 selected papers, we compare important performance properties of the proposed algorithms related to the vessel and the environment it is operating in. We also analyse how safety is incorporated, and what components constitute the objective function in these algorithms. Finally, we focus on comparing advantages and limitations of the 45 analysed papers. A key finding is the need for a unified platform for evaluating and comparing the performance of algorithms under a large set of possible real-world scenarios.

scholarly journals A Study on Path Planning Algorithms of UAV Collision Avoidance

2019 ◽  
Vol 37 (1) ◽  
pp. 100-106
Author(s):  
Zhao Xu ◽  
Jinwen Hu ◽  
Yunhong Ma ◽  
Man Wang ◽  
Chunhui Zhao
Keyword(s):  
Path Planning ◽  
Collision Avoidance ◽  
Potential Field ◽  
Ant Colony Algorithm ◽  
Artificial Potential Field ◽  
Fuzzy Logic Algorithm ◽  
Aerial Vehicle ◽  
Simulation Results ◽  
Planning Algorithms ◽  
Dynamic Obstacle

The unmanned aerial vehicle (UAV) has been a research hotspot worldwide. The UAV system is developing to be more and more intelligent and autonomous. UAV path planning is an important part of UAV autonomous control and the important guarantee of UAV's safety. For the purpose of improving the collision avoidance and path planning algorithms, the artificial potential field, fuzzy logic algorithm and ant colony algorithm are simulated respectively in the static obstacle and dynamic obstacle environments, and compared based on the minimum avoidance distance and range ratio. Meanwhile, an improved algorithm of artificial potential field is proposed, and the improvement helps the UAV escape the local minimum by introducing the vertical guidance repulsion. The simulation results are rigorous and reliable, which lay a foundation for the further fusion of multiple algorithms and improving the path planning algorithms.

scholarly journals Pursuit predation with intermittent locomotion in zebrafish

2020 ◽  
pp. jeb.230623 ◽  
Author(s):  
Alberto P. Soto ◽  
Matthew J. McHenry
Keyword(s):  
Path Planning ◽  
Danio Rerio ◽  
Control Strategy ◽  
Autonomous Robots ◽  
Continuous Motion ◽  
Pure Pursuit ◽  
Burst Phase ◽  
Planning Algorithms ◽  
And Control

The control of a predator's locomotion is critical to its ability to capture prey. Flying animals adjust their heading continuously with control similar to guided missiles. However, many animals do not move with rapid continuous motion, but rather interrupt their progress with frequent pauses. To understand how such intermittent locomotion may be controlled during predation, we examined the kinematics of zebrafish (Danio rerio) as they pursued larval prey of the same species. Like many fishes, zebrafish move with discrete burst-and-coast swimming. We found that the change in heading and tail excursion during the burst phase was linearly related to the prey's bearing. These results suggest a strategy, which we call intermittent pure pursuit, that offers advantages in sensing and control. This control strategy is similar to perception and path-planning algorithms required in the design of some autonomous robots and may be common to a diversity of animals.

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