USV Dynamic Accurate Obstacle Avoidance Based on Improved Velocity Obstacle Method

Wang, Jia; Wang, Rongtao; Lu, Dawei; Zhou, Hao; Tang, Tao

doi:10.3390/electronics11172720

Cited by 13 publications

(7 citation statements)

References 29 publications

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“…In this paper, carbon plate material is used as the frame of the aerial robot to reduce its weight of the aerial robot, and the design of the outer ring protective frame is added to improve the use frequency of the sensor and greatly improve the endurance of the aerial robot [3][4][5][6]. In addition, the four axis rotor "X" structure is adopted to avoid the phenomenon that the acceleration time is too long and the sensor is blocked due to the "+" structure [7][8][9].…”

Section: Aerial Robot Modelmentioning

confidence: 99%

Obstacle Avoidance Design of Aerial Robot Combining A star algorithm Algorithm and Optical Dynamic Capture Method

Shi

Cai²,

Yuan³

2023

J. Phys.: Conf. Ser.

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The traditional A star obstacle avoidance algorithm is based on binocular cameras for indoor positioning, which requires rich obstacle feature points and has the risk of explosion in a single indoor environment. In this paper, the method of merging the A star algorithm and optical dynamic capture is proposed. By pasting Marker points on key moving parts, the actual position of the aerial robot is calculated with the optical dynamic capture system, and compared with the target position planned by the A star algorithm and corrected in real time during a flight. Through the experimental analysis of the original acceleration of the aerial robot and different position between the target point and the actual point in the flight process, the stability and flight accuracy of the aerial robot in the flight process can be significantly improved, which has good practical application value.

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Section: Aerial Robot Modelmentioning

confidence: 99%

Obstacle Avoidance Design of Aerial Robot Combining A star algorithm Algorithm and Optical Dynamic Capture Method

Shi

Cai²,

Yuan³

2023

J. Phys.: Conf. Ser.

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“…Aiming at the problem that the VO algorithm does not consider the dynamic obstacles, Kuwata et al [18] proposed a method to identify the speed and direction of dynamic obstacles based on COLREGS to achieve obstacle avoidance. Wang et al [19] proposed a special triangular obstacle geometric model to reconstruct the velocity obstacle area. The collision time is predicted by combining the previously collected data with the distance, course and other relevant data of the detected obstacles.…”

Section: Introductionmentioning

confidence: 99%

LSDA-APF: A Local Obstacle Avoidance Algorithm for Unmanned Surface Vehicles Based on 5G Communication Environment

Li,

Jiao,

et al. 2024

Computer Modeling in Engineering &Amp; Sciences

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In view of the complex marine environment of navigation, especially in the case of multiple static and dynamic obstacles, the traditional obstacle avoidance algorithms applied to unmanned surface vehicles (USV) are prone to fall into the trap of local optimization. Therefore, this paper proposes an improved artificial potential field (APF) algorithm, which uses 5G communication technology to communicate between the USV and the control center. The algorithm introduces the USV discrimination mechanism to avoid the USV falling into local optimization when the USV encounter different obstacles in different scenarios. Considering the various scenarios between the USV and other dynamic obstacles such as vessels in the process of performing tasks, the algorithm introduces the concept of dynamic artificial potential field. For the multiple obstacles encountered in the process of USV sailing, based on the International Regulations for Preventing Collisions at Sea (COLREGS), the USV determines whether the next step will fall into local optimization through the discrimination mechanism. The local potential field of the USV will dynamically adjust, and the reverse virtual gravitational potential field will be added to prevent it from falling into the local optimization and avoid collisions. The objective function and cost function are designed at the same time, so that the USV can smoothly switch between the global path and the local obstacle avoidance. The simulation results show that the improved APF algorithm proposed in this paper can successfully avoid various obstacles in the complex marine environment, and take navigation time and economic cost into account.

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“…The current local path planning algorithms mainly include fuzzy logic algorithm [26][27], artificial potential field method [28][29][30][31], velocity obstacle method [32][33] and so on. Guan et al proposed a ship domain model based on fuzzy logic aimed at providing early warning of ship collision risk and a reasonable reference that can be used in combination with the International Regulation for Preventing Collisions at Sea [26].…”

Section: Introductionmentioning

confidence: 99%

“…Zhou et al proposed a method of removing the shaking state based on a favorable path, and on this basis, visibility graph method is used to optimize the path of the AUV to avoid obstacles [31]. Wang et al proposed a USV autonomous dynamic obstacle avoidance method based on the enhanced velocity obstacle method in order to achieve path replanning [32].…”

Section: Introductionmentioning

confidence: 99%

Ship Formation Algorithm Based on the Leader–Follower Method

Meng

Chen³

et al. 2023

IEEE Access

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In recent years, marine engineers have increasingly relied on multiship collaborative work to complete complex tasks at sea and improve maritime transport efficiency. Ship formation significantly contributes to the maintenance of stability during multiship-coordinated operations, but establishing the formation structure while ensuring the safety of each ship remains challenging. Therefore, this study proposes an improved leader-follower-based formation algorithm as a solution to this issue. First, the fast marching square method was used for global static path planning. The leader-follower formation control method then enabled the path tracking of the follower ship to the leader ship. Finally, an improved artificial potential field method was used for local collision avoidance, and virtual obstacles were added to improve the situation in which the ship probably entered a local minimum point. The experimental results revealed that the proposed algorithm could plan a route with time, smoothness, and safety advantages for the formation leader and quickly form a stable formation. Notably, the ship can quickly initiate collision avoidance operations when it encounters an obstacle posing a collision risk.INDEX TERMS Artificial potential field method, fast marching square method, formation of ships, leaderfollower method, local collision, path planning.

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USV Dynamic Accurate Obstacle Avoidance Based on Improved Velocity Obstacle Method

Cited by 13 publications

References 29 publications

Obstacle Avoidance Design of Aerial Robot Combining A star algorithm Algorithm and Optical Dynamic Capture Method

Obstacle Avoidance Design of Aerial Robot Combining A star algorithm Algorithm and Optical Dynamic Capture Method

LSDA-APF: A Local Obstacle Avoidance Algorithm for Unmanned Surface Vehicles Based on 5G Communication Environment

Ship Formation Algorithm Based on the Leader–Follower Method

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