scholarly journals Artificial potential field-based swarm finding of the unmanned surface vehicles in the dynamic ocean environment

2020 ◽  
Vol 17 (3) ◽  
pp. 172988142092530
Author(s):  
Guoge Tan ◽  
Jiayuan Zhuang ◽  
Jin Zou ◽  
Lei Wan ◽  
Zhiyuan Sun
Keyword(s):  
Numerical Simulations ◽  
Collision Avoidance ◽  
Potential Field ◽  
Advanced Technology ◽  
Artificial Potential Field ◽  
Unmanned Surface Vehicle ◽  
Unmanned Surface Vehicles ◽  
Field Force ◽  
International Regulations ◽  
Ocean Environment

Using multiple unmanned surface vehicle swarms to implement tasks cooperatively is the most advanced technology in recent years. However, how to find which swarm the unmanned surface vehicle belongs to is a meaningful job. So, this article proposed an artificial potential field-based swarm finding algorithm, which applies the potential field force directly to unmanned surface vehicles and leads them to their belonging swarm quickly and accurately. Meanwhile, the proposed algorithm can also maintain the formation stable while following the desired path. Based on the swarm finding algorithm, the artificial potential field-based collision avoidance method and the International Regulations for Preventing Collisions at Sea-based dynamic collision avoidance strategy are applied to the swarm control of multi-unmanned surface vehicles to enhance the performance in the dynamic ocean environment. Methods in this article are verified through numerical simulations to illustrate the feasibility and effectiveness of proposed schemes.

scholarly journals An Efficient Ship Automatic Collision Avoidance Method Based on Modified Artificial Potential Field

2021 ◽  
Vol 10 (1) ◽  
pp. 3
Author(s):  
Zhongxian Zhu ◽  
Hongguang Lyu ◽  
Jundong Zhang ◽  
Yong Yin
Keyword(s):  
Collision Avoidance ◽  
Potential Field ◽  
Repulsive Force ◽  
Adjustable Parameter ◽  
Artificial Potential Field ◽  
Force Model ◽  
Safe Distance ◽  
International Regulations ◽  
Motion Characteristics ◽  
Approach Time

A novel collision avoidance (CA) algorithm was proposed based on the modified artificial potential field (APF) method, to construct a practical ship automatic CA system. Considering the constraints of both the International Regulations for Preventing Collisions at Sea (COLREGS) and the motion characteristics of the ship, the multi-ship CA algorithm was realized by modifying the repulsive force model in the APF method. Furthermore, the distance from the closest point of approach-time to the closest point of approach (DCPA-TCPA) criterion was selected as the unique adjustable parameter from the perspective of navigation practice. Collaborative CA experiments were designed and conducted to validate the proposed algorithm. The results of the experiments revealed that the actual DCPA and TCPA agree well with the parameter setup that keeps the ship at a safe distance from other ships in complex encountering situations. Consequently, the algorithm proposed in this study can achieve efficient automatic CA with minimal parameter settings. Moreover, the navigators can easily accept and comprehend the adjustable parameters, enabling the algorithm to satisfy the demand of the engineering applications.

scholarly journals Collision Avoidance Algorithm Based on COLREGs for Unmanned Surface Vehicle

2021 ◽  
Vol 9 (8) ◽  
pp. 863
Author(s):  
Hyo-Gon Kim ◽  
Sung-Jo Yun ◽  
Young-Ho Choi ◽  
Jae-Kwan Ryu ◽  
Jin-Ho Suh
Keyword(s):  
Collision Avoidance ◽  
Unmanned Surface Vehicle ◽  
Unmanned Surface Vehicles ◽  
International Regulations ◽  
Window Approach

Recently, unmanned surface vehicles (USV) are being actively developed. For USVs to be put to practical use, it is necessary to secure safety by preventing collisions with general ships. To this end, USVs must avoid opposing vessels based on international regulations for preventing collisions at sea (COLREGs, 1972). This paper proposes an algorithm for USVs to avoid collisions with opposing vessels based on COLREG rules. The proposed algorithm predicts dangerous situations based on distance to closest point of approach (DCPA) and time to closest point of approach (TCPA). It allows USVs to avoid opponent ships based on the dynamic window approach (DWA). The DWA has been improved to comply with COLREGs, and we implemented a simulation and compared the standard DWA with the COLREG-compliant DWA (CCDWA) proposed in this paper. The results confirm that the CCDWA complies with COLREGs.

scholarly journals Collision avoidance planning for unmanned surface vehicle based on eccentric expansion

2019 ◽  
Vol 16 (3) ◽  
pp. 172988141985194 ◽  
Author(s):  
Lifei Song ◽  
Zhuo Chen ◽  
Zaopeng Dong ◽  
Zuquan Xiang ◽  
Yunsheng Mao ◽  
...  
Keyword(s):  
Collision Avoidance ◽  
Obstacle Avoidance ◽  
Physical Simulation ◽  
Risk Level ◽  
Unmanned Surface Vehicle ◽  
Unmanned Surface Vehicles ◽  
Automatic Driving ◽  
International Regulations ◽  
Dynamic Obstacle Avoidance ◽  
Dynamic Obstacle

The International Regulations for Preventing Collisions at Sea (COLREGS) specify certain navigation rules for ships at risk for collision. Theoretically, the safety of unmanned surface vehicles and traffic boats would be guaranteed when they comply with the COLREGS. However, if traffic boats do not comply with the demands of the convention, thereby increasing the danger level, then adhering to the COLREGS may be dangerous for the unmanned surface vehicle. In this article, a dynamic obstacle avoidance algorithm for unmanned surface vehicles based on eccentric expansion was developed. This algorithm is used to solve the possible failure of collision avoidance when the unmanned surface vehicle invariably obeys the COLREGS during the avoidance process. An obstacle avoidance model based on the velocity obstacle method was established. Thereafter, an eccentric expansion operation on traffic boats was proposed to ensure a reasonable balance between safety and the rules of COLREGS. The expansion parameters were set according to the rules of COLREGS and the risk level of collision. Then, the collision avoidance parameters were calculated based on the aforementioned motion model. With the use of MATLAB and Unity software, a semi-physical simulation platform was established to perform the avoidance simulation experiment under different situations. Results show the validity, reliability and intellectuality of the algorithm. This research can be used for intelligent collision avoidance of unmanned surface vehicle and other automatic driving ships.

Optimized artificial potential field algorithm to multi-unmanned aerial vehicle coordinated trajectory planning and collision avoidance in three-dimensional environment

2019 ◽  
Vol 233 (16) ◽  
pp. 6032-6043 ◽  
Author(s):  
Jun Tang ◽  
Jiayi Sun ◽  
Cong Lu ◽  
Songyang Lao
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Collision Avoidance ◽  
Unmanned Aerial Vehicle ◽  
Trajectory Planning ◽  
Potential Field ◽  
Three Dimensional ◽  
Artificial Potential Field ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
Vehicle Trajectory

Multi-unmanned aerial vehicle trajectory planning is one of the most complex global optimum problems in multi-unmanned aerial vehicle coordinated control. Results of recent research works on trajectory planning reveal persisting theoretical and practical problems. To mitigate them, this paper proposes a novel optimized artificial potential field algorithm for multi-unmanned aerial vehicle operations in a three-dimensional dynamic space. For all purposes, this study considers the unmanned aerial vehicles and obstacles as spheres and cylinders with negative electricity, respectively, while the targets are considered spheres with positive electricity. However, the conventional artificial potential field algorithm is restricted to a single unmanned aerial vehicle trajectory planning in two-dimensional space and usually fails to ensure collision avoidance. To deal with this challenge, we propose a method with a distance factor and jump strategy to resolve common problems such as unreachable targets and ensure that the unmanned aerial vehicle does not collide into the obstacles. The method takes companion unmanned aerial vehicles as the dynamic obstacles to realize collaborative trajectory planning. Besides, the method solves jitter problems using the dynamic step adjustment method and climb strategy. It is validated in quantitative test simulation models and reasonable results are generated for a three-dimensional simulated urban environment.

scholarly journals UAV Group Formation Collision Avoidance Method Based on Second-Order Consensus Algorithm and Improved Artificial Potential Field

Symmetry ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1162 ◽  
Author(s):  
Yang Huang ◽  
Jun Tang ◽  
Songyang Lao
Keyword(s):  
Collision Avoidance ◽  
Potential Field ◽  
Group Formation ◽  
Target Position ◽  
Field Method ◽  
Second Order ◽  
Consensus Algorithm ◽  
Artificial Potential Field ◽  
Potential Field Method ◽  
Artificial Potential Field Method

The problem of collision avoidance of an unmanned aerial vehicle (UAV) group is studied in this paper. A collision avoidance method of UAV group formation based on second-order consensus algorithm and improved artificial potential field is proposed. Based on the method, the UAV group can form a predetermined formation from any initial state and fly to the target position in normal flight, and can avoid collision according to the improved smooth artificial potential field method when encountering an obstacle. The UAV group adopts the “leader–follower” strategy, that is, the leader UAV is the controller and flies independently according to the mission requirements, while the follower UAV follows the leader UAV based on the second-order consensus algorithm and formations gradually form during the flight. Based on the second-order consensus algorithm, the UAV group can achieve formation maintenance easily and the Laplacian matrix used in the algorithm is symmetric for an undirected graph. In the process of obstacle avoidance, the improved artificial potential field method can solve the jitter problem that the traditional artificial potential field method causes for the UAV and avoids violent jitter. Finally, simulation experiments of two scenarios were designed to verify the collision avoidance effect and formation retention effect of static obstacles and dynamic obstacles while the two UAV groups fly in opposite symmetry in the dynamic obstacle scenario. The experimental results demonstrate the effectiveness of the proposed method.

Research on active collision avoidance algorithm for intelligent vehicle based on improved artificial potential field model

2020 ◽  
Vol 17 (3) ◽  
pp. 172988142091123
Author(s):  
Chaochun Yuan ◽  
Shuofeng Weng ◽  
Jie Shen ◽  
Long Chen ◽  
Youguo He ◽  
...  
Keyword(s):  
Collision Avoidance ◽  
Potential Field ◽  
Field Method ◽  
Superior Performance ◽  
Intelligent Vehicle ◽  
Artificial Potential Field ◽  
Sideslip Angle ◽  
Lane Changing ◽  
Model Based ◽  
Braking Process

In this article, an active collision avoidance based on improved artificial potential field is proposed to satisfy collision avoidance for intelligent vehicle. A longitudinal safety distance model based on analysis of braking process and a lane-changing safety spacing model based on minimum time of lane changing under the constraint of sideslip angle are presented. In addition, an improved artificial potential field method is introduced, which represents the influence of environmental information with artificial force. Simulation results demonstrate the superior performance of the proposed algorithm over collision avoidance for intelligent vehicle.

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