Intelligent Vector Field Histogram based collision avoidance method for AUV

Zhang, Gengshi; Zhang, Yonggang; Xu, Jing; Chen, Tao; Zhang, Wei; Xing, Wen

doi:10.1016/j.oceaneng.2022.112525

Cited by 11 publications

(2 citation statements)

References 27 publications

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“…Furthermore, the VFH+ algorithm eliminates the fluctuations in the steering direction that affected the VFF, thanks to a smoothing approach applied to the polar histogram itself [64][65][66][67][68][69][70][71]. However, the VFH also has its drawbacks.…”

Section: Related Workmentioning

confidence: 99%

Design of an Assisted Driving System for Obstacle Avoidance Based on Reinforcement Learning Applied to Electrified Wheelchairs

Pacini,

Dini,

Fanucci

2024

Electronics

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Driving a motorized wheelchair is not without risk and requires high cognitive effort to obtain good environmental perception. Therefore, people with severe disabilities are at risk, potentially lowering their social engagement, and thus, affecting their overall well-being. Therefore, we designed a cooperative driving system for obstacle avoidance based on a trained reinforcement learning (RL) algorithm. The system takes the desired direction and speed from the user via a joystick and the obstacle distribution from a LiDAR placed in front of the wheelchair. Considering both inputs, the system outputs a pair of forward and rotational speeds that ensure obstacle avoidance while being as close as possible to the user commands. We validated it through simulations and compared it with a vector field histogram (VFH). The preliminary results show that the RL algorithm does not disruptively alter the user intention, reduces the number of collisions, and provides better door passages than a VFH; furthermore, it can be integrated on an embedded device. However, it still suffers from higher jerkiness.

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Section: Related Workmentioning

confidence: 99%

Design of an Assisted Driving System for Obstacle Avoidance Based on Reinforcement Learning Applied to Electrified Wheelchairs

Pacini,

Dini,

Fanucci

2024

Electronics

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“…Wu et al [24] used shipborne laser radar to quickly identify dynamic obstacles, and optimize candidate directions by considering USV velocity vector and dynamic obstacles through VFH+ method to avoid obstacles, but this method may still fall into local optimization in solving complex environment. Zhang et al [25] proposed a method of intelligent vector field histogram (IVFH) to achieve collision avoidance of autonomous underwater vehicle (AUV) in underwater 3D dynamic space. The directed cuboid static obstacle environment model was introduced to improve the efficiency of collision avoidance decision-making.…”

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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Improved dynamic windows approach based on energy consumption management and fuzzy logic control for local path planning of mobile robots

Yao,

Deng,

Feng

et al. 2024

Computers & Industrial Engineering

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Intelligent Vector Field Histogram based collision avoidance method for AUV

Cited by 11 publications

References 27 publications

Design of an Assisted Driving System for Obstacle Avoidance Based on Reinforcement Learning Applied to Electrified Wheelchairs

Design of an Assisted Driving System for Obstacle Avoidance Based on Reinforcement Learning Applied to Electrified Wheelchairs

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

Improved dynamic windows approach based on energy consumption management and fuzzy logic control for local path planning of mobile robots

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