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- 저자 : Zhiyao Xu (검색결과 3 건)
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Smooth Path Planning Method for Unmanned Surface Vessels Considering Environmental Disturbance
Jiabin Yu,Zhihao Chen,Zhiyao Zhao,Xiaoyi Wang,Yuting Bai,Jiguang Wu,Jiping Xu 제어·로봇·시스템학회 2023 International Journal of Control, Automation, and Vol.21 No.10
To solve the problems of unsmooth path planning, insufficient dynamic obstacle avoidance ability, and environmental disturbance effect on the path planning result, this paper proposes a smooth path planning method for unmanned surface vessels (USVs) considering environmental disturbance. First, an improved A* algorithm, which uses the path smoothing method based on the minimum turning radius of a USV, is proposed for global path planning. The binary tree method is used instead of the enumeration method to select a relatively optimal path in the current situation to improve algorithm efficiency. In addition, the dynamic window approach (DWA) with the Convention on the International Regulation for Preventing Collision at Sea (COLREGs) constraints is used for local path planning. The dist function in the DWA algorithm is improved to enhance the DWA algorithm’s ability to avoid dynamic obstacles. Finally, the environmental disturbance function is derived and added to the A* and DWA algorithms to handle the effect of environmental disturbances, such as water flow, on the path planning result, which can significantly improve the path-planning ability of the algorithm in the presence of environmental disturbances. Simulation experiments are performed in three scenarios to verify the proposed algorithm. The experimental results show that compared with the other algorithms, the proposed algorithm can effectively avoid dynamic obstacles and reduce the impact of environmental disturbance on the path planning result. At the same time, the proposed algorithm has high efficiency and strong robustness.
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A Path Planning Method for Unmanned Surface Vessels in Dynamic Environment
Jiabin Yu,Zhihao Chen,Zhiyao Zhao,Jiping Xu,Yang Lu 제어·로봇·시스템학회 2024 International Journal of Control, Automation, and Vol.22 No.4
A path planning method for unmanned surface vessels (USV) in dynamic environment is proposed to address the impact of dynamic environments on path planning results and the lack of dynamic obstacle avoidance capabilities. First, the considering ocean current rapidly exploring random tree (RRT*) (COC-RRT*) algorithm was proposed for global path planning. The RRT* algorithm has been enhanced with the integration of the virtual field sampling algorithm and ocean current constraint algorithm. The COC-RRT* algorithm optimizes the global planning path by adjusting the path between the parent nodes and child nodes. Second, according to the limitations of the International Regulations for Preventing Collisions at Sea (COLREGs), the improved dynamic window approach (DWA) is applied for local path planning. To enhance the ability of avoid dynamic obstacles, the dist function in the DWA algorithm has been improved. Simulation experiments were conducted in three scenarios to validate the proposed algorithm. The experimental results demonstrate that, in comparison with other algorithms, the proposed algorithm effectively avoids dynamic obstacles and mitigates the influence of the space-varying ocean current environment on the path-planning outcome. Additionally, the proposed algorithm exhibits high efficiency and robustness. The results verified the effectiveness of the proposed algorithm in dynamic environments.
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Chong Chen,Shimin Zhang,Xiaoxiao Zhu,Jingyu Shen,Zhiyao Xu 한국정밀공학회 2020 International Journal of Precision Engineering and Vol.21 No.5
Many patients with stroke are suff ering lower limb locomotor dysfunctions all over the world. Body weight supported treadmilltraining has proven to be an eff ective post-stroke rehabilitation training method for these people’s recovery. Nowadays,lower extremity rehabilitation exoskeleton composed of a pair of mechanical legs has been introduced into body weightsupported treadmill training, which can guide and assist the movements of the patient’s legs. However, active movementsof the patient are hardly to be achieved when the rehabilitation exoskeleton is controlled by a commonly utilized positionbasedpassive strategy. Considering the restriction above, a weight supported rehabilitation training exoskeleton device wasdesigned in this paper to ensure the stroke patient can participate in rehabilitation training voluntarily. To realize this goal,a patient-cooperative rehabilitation training strategy based on adaptive impedance control is adopted for the swing phase inthe training. Human–exoskeleton interaction torques are evaluated by a backpropagation neural network and a disturbanceobserver whose stability is proved by Lyapunov’s law. With no additional demand of interaction torque sensors, the complexityof this system is simplifi ed and the cost is reduced. In order to promote the involvement of patient during the rehabilitationtraining, fuzzy algorithm is used to adjust the impedance parameters according to the human–exoskeleton interaction torques. The eff ectiveness of the whole rehabilitation control strategy is demonstrated by experimental results.
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