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Full-Text Articles in Systems Science
Improvement Of A* Algorithm In Path Planning Of Mobile Robot, Dexin Yao, Hongjun San, Yaru Wang, Haijie Sun, Jiupeng Chen, Xiaoyuan Yang
Improvement Of A* Algorithm In Path Planning Of Mobile Robot, Dexin Yao, Hongjun San, Yaru Wang, Haijie Sun, Jiupeng Chen, Xiaoyuan Yang
Journal of System Simulation
Abstract: To solve the problems of excessively redundant nodes, low search efficiency, and excessive path turning angle in the path search of the traditional A* algorithm, an improved A* algorithm is proposed to plan the optimal path. First, the amount of search neighborhood of the A* algorithm is increased to 24 to obtain a more accurate and comprehensive search field. Second, the angle search algorithm is introduced, eliminating the unnecessary nodes in the path search and making the search more target-oriented. Third, the heuristic function is weighted by the exponential attenuation through the relative position of the current point and …
Garage Agv Path Planning And Simulation Based On Improved Dwa, Zongfang Ma, Linxuan Zhang, Lin Song, Jia Wang
Garage Agv Path Planning And Simulation Based On Improved Dwa, Zongfang Ma, Linxuan Zhang, Lin Song, Jia Wang
Journal of System Simulation
Abstract: Aiming at the path planning and real-time obstacle avoidance of AGV in complex path environment of intelligent garage, an improved hybrid algorithm combining ant colony algorithm and dynamic window method is proposed. In the global planning, the adaptive adjustment of pheromone volatilization coefficient and the fusion of angle parameters are introduced to establish the garage direction pheromone matrix to increase the guidance ability of target points, expand the direction selectivity of ants. In the local planning, the improved DWA of the obstacle distance evaluation subfunction based on elliptic equation is designed. By extracting the global path node of the …
Unmanned Vehicle Path Planning And Tracking Control Based On Improved Artificial Potential Field Method, Minghao Guo, Peng Ji, Haiwei Huang
Unmanned Vehicle Path Planning And Tracking Control Based On Improved Artificial Potential Field Method, Minghao Guo, Peng Ji, Haiwei Huang
Journal of System Simulation
Abstract: A path planning algorithm based on improved artificial potential field method and a tracking control strategy based on model predictive controller are proposed for the unmanned vehicle avoiding dynamic obstacles in the complex scene of lane changing and overtaking. The theory of safety ellipse and the concept of prediction distance are introduced to adjust the influence region of potential field. By adding velocity potential field to change potential field function, the problem of vehicle avoiding dynamic obstacles is solved. Based on the linear three-degree-of-freedom vehicle dynamics model, a model prediction controller including potential field environment is established. The effectiveness …
Path Planning Based On Improved A* And Dynamic Window Approach, Peng Ji, Xinyuan Zhang, Shuaixuan Gao, Shuorang Wei
Path Planning Based On Improved A* And Dynamic Window Approach, Peng Ji, Xinyuan Zhang, Shuaixuan Gao, Shuorang Wei
Journal of System Simulation
Abstract: In response to the low efficiency, redundant turning points, and collision issues of the traditional A* algorithm, a smart vehicle path planning algorithm that integrates an improved A* algorithm with a dynamic window approach has been proposed. The algorithm has enhanced the search point selection method, optimized the evaluation function, selected key turning points based on the slope values between turning points, and removed redundant turning points. Between every two optimized key turning points, a dynamic window approach that balances speed and safety is used for local obstacle avoidance. Experiments show that compared to the traditional A* algorithm, this …
An Improved Path Planning Algorithm For Mobile Robots, Haijie Sun, Hongjun San, Le Xiao, Dexin Yao, Jiupeng Chen, Xiaoyuan Yang
An Improved Path Planning Algorithm For Mobile Robots, Haijie Sun, Hongjun San, Le Xiao, Dexin Yao, Jiupeng Chen, Xiaoyuan Yang
Journal of System Simulation
Abstract: To solve the problems of invalid sampling and non-optimal paths of the RRT, the quasi-stream avoidance algorithm is proposed. The RRT algorithm is introduced to specify the sampling interval to limit the sampling points and enhance the goal-oriented nature of sampling. The quasi-stream avoidance algorithm incorporating the A* algorithm (QSA*) is used to quickly bypass the obstacle when it is encountered. A path optimization algorithm is used to smooth the searched path. The simulation results show that compared with the RRT algorithm, the computation time of the RRT-QSA* algorithm is reduced by 96.83%~99.88%, the number of search nodes is …
Multi-Step Information Aided Q-Learning Path Planning Algorithm, Yuelong Wang, Songyan Wang, Tao Chao
Multi-Step Information Aided Q-Learning Path Planning Algorithm, Yuelong Wang, Songyan Wang, Tao Chao
Journal of System Simulation
Abstract: To improve the path planning capability of mobile robots in a static environment and solve the problem of slow convergence of the traditional Q-learning algorithm in path planning, this paper proposes a multi-step information-aided Q-learning improvement algorithm. Using the multi-step information of greedy action in ε -greedy strategy and length of the historical optimal path to update the eligibility traces, which makes the effective eligibility traces work continuously in the iteration of the algorithm and solves the loop traps that may fall into with the preserved multi-step information; using the local multiflower pollination algorithm to initialize the Q-value table …
Visual Robot Obstacle Avoidance Planning And Simulation Using Mapped Point Clouds, Hanlin Huo, Xiangjun Zou, Yan Chen, Xinzhao Zhou, Mingyou Chen, Chengen Li, Yaoqiang Pan, Yunchao Tang
Visual Robot Obstacle Avoidance Planning And Simulation Using Mapped Point Clouds, Hanlin Huo, Xiangjun Zou, Yan Chen, Xinzhao Zhou, Mingyou Chen, Chengen Li, Yaoqiang Pan, Yunchao Tang
Journal of System Simulation
Abstract: In response to the large and complex data volume and high redundancy of visual point cloud obstacle recognition in complex unstructured orchard environments, which severely impacts the real-time performance and efficiency of harvesting operations, a point cloud compression algorithm is proposed based on point cloud segmentation to enhance the efficiency of point cloud obstacle recognition and environmental adaptability. An Informed RRT* based approach is used combined with an inverse projection algorithm, mapping-based informed RRT*(M-Informed RRT*) to solve the harvesting path problem. By constructing a highly real-time and robust integrated robot system for sampling, perception, and obstacle avoidance, efficient obstacle …
Fusion Of Improved A* And Dynamic Window Approach For Mobile Robot Path Planning, Rongshen Lai, Lei Dou, Zhiyong Wu, Shuai Sun
Fusion Of Improved A* And Dynamic Window Approach For Mobile Robot Path Planning, Rongshen Lai, Lei Dou, Zhiyong Wu, Shuai Sun
Journal of System Simulation
Abstract: The traditional A* algorithm is computationally simple and has short planning paths, but it still suffers from redundancy of inflection points, low search efficiency and zigzagging planning paths. Aiming at the above problems, a fusion algorithm combining the improved A* algorithm and the improved dynamic window approach is proposed for the path planning of mobile robots. For the problem of redundant inflection points, the key nodes are extracted to effectively remove the useless inflection points; for the problem of low search efficiency, a dynamic weighting factor is introduced into the heuristic function of the evaluation function, which changes the …
Research On Virtual Simulation Testing Technology For Intelligent Navigation Collision Avoidance Decision-Making And Planning, Jialun Liu, Fan Yang, Lingli Xie, Shijie Li, Tengfei Wang
Research On Virtual Simulation Testing Technology For Intelligent Navigation Collision Avoidance Decision-Making And Planning, Jialun Liu, Fan Yang, Lingli Xie, Shijie Li, Tengfei Wang
Journal of System Simulation
Abstract: This paper studies virtual simulation testing technology for intelligent navigation collision avoidance decision-making and planning. The application requirements of intelligent navigation in cargo ships are introduced, and the current research status of collision avoidance decision-making strategies, path planning algorithms and decision-making planning testing technology are analyzed. For the intelligent navigation collision avoidance decision-making and planning capabilities of cargo ships, an intelligent navigation collision avoidance decision-making and planning algorithm is proposed based on the encounter situation division in the collision avoidance rules, combined with the quaternary ship field and Bezier curve interpolation theory. A simulation testing method for decision-making planning …
Uav Dynamic Path Planning Algorithm Combined With Dynamic Window Approach, Bin Liu, Ying Lan, Wentao Huang, Qinqin Fan
Uav Dynamic Path Planning Algorithm Combined With Dynamic Window Approach, Bin Liu, Ying Lan, Wentao Huang, Qinqin Fan
Journal of System Simulation
Abstract: To solve the problem of the poor search for optimal performance and obstacle avoidance ability of path planning algorithms in complex dynamic environments, a UAV dynamic path planning algorithm combined with dynamic window approach (UAV-DPPA-DWA) is proposed. In the UAVDPPA- DWA algorithm, a novel elliptic tangent graph algorithm based on the evaluation of offset degree and obstacle distance is proposed to obtain the optimal guidance path for the UAV in static environments. If the UAV detects moving obstacles, a localized obstacle avoidance trajectory will be generated using the dynamic window method with adaptive parameters. Otherwise, the UAV will continue …
Path Planning For Mobile Robot Based On Angle Search, Yaru Wang, Dexin Yao, Zengli Liu, Yi Peng
Path Planning For Mobile Robot Based On Angle Search, Yaru Wang, Dexin Yao, Zengli Liu, Yi Peng
Journal of System Simulation
Abstract: The angle search algorithm for angle-controlled robots is proposed to increase the path search speed and optimize the path length. The algorithm effectively finds a path in static surroundings by performing an efficient search in a specific dimensional range based on the position of the robot and the target point. Firstly, search angles are predetermined according to the characteristics of the environment in the grid map. Then, the estimated angle of the robot's surrounding grid is computed. Finally, a new extension point is chosen by comparing the estimated angle to the search angle, demonstrating the usefulness and viability of …
Research On Path Planning Of Warehouse Robot With Improved Harris Hawks Algorithm, Xu Lei, Jingyi Chen, Xiaoyang Chen
Research On Path Planning Of Warehouse Robot With Improved Harris Hawks Algorithm, Xu Lei, Jingyi Chen, Xiaoyang Chen
Journal of System Simulation
Abstract: To improve the path planning efficiency of warehouse mobile robots in static environments, and to solve the problems of slow convergence and local optimum of traditional Harris Hawk (HHO) algorithm in path planning, a Harris Hawk optimization algorithm based on Tent chaotic mapping fused with Cauchy's back-learning variant (TCLHHO) is proposed. The population diversity is increased by Tent Chaotic mapping to speed up convergence. An exponential prey escape energy updating strategy is proposed to balance the global search and local exploitation capabilities of the algorithm. The optimal individual is disturbed by Cauchy mutation operator and inverse learning strategy to …
Research On Collaborative Optimization Method Of Multi-Uav Task Allocation And Path Planning, Peng Xiao, Feng Xie, Haihong Ni, Min Zhang, Zhili Tang, Ni Li
Research On Collaborative Optimization Method Of Multi-Uav Task Allocation And Path Planning, Peng Xiao, Feng Xie, Haihong Ni, Min Zhang, Zhili Tang, Ni Li
Journal of System Simulation
Abstract: Aiming at the task requirements of multi-UAV to perform multi-target collaborative reconnaissance, a collaborative optimization method of multi-machine and multi-objective task allocation and path planning is proposed. Based on the partheno genetic algorithms (PGA), a cost function combined with the actual path cost is constructed through the Dubins curve. To further reduce the calculation cost, a clustering algorithm based on UAV detection distance is proposed, and the generated clustering point is used as a new waypoint of UAV. The simulation results show that considering the dangerous area and the large number of reconnaissance points, the algorithm can effectively complete …
Deep Learning Based Local Path Planning Method For Moving Robots, Zesen Liu, Sheng Bi, Chuanhong Guo, Yankui Wang, Min Dong
Deep Learning Based Local Path Planning Method For Moving Robots, Zesen Liu, Sheng Bi, Chuanhong Guo, Yankui Wang, Min Dong
Journal of System Simulation
Abstract: In order to integrate visual information into the robot navigation process, improve the robot's recognition rate of various types of obstacles, and reduce the occurrence of dangerous events, a local path planning network based on two-dimensional CNN and LSTM is designed, and a local path planning approach based on deep learning is proposed. The network uses the image from camera and the global path to generate the current steering angle required for obstacle avoidance and navigation. A simulated indoor scene is built for training and validating the network. A path evaluation method that uses the total length and the …
Path Planning Of Unmanned Delivery Vehicle Based On Improved Q-Learning Algorithm, Xiaokang Wang, Jie Ji, Yang Liu, Qing He
Path Planning Of Unmanned Delivery Vehicle Based On Improved Q-Learning Algorithm, Xiaokang Wang, Jie Ji, Yang Liu, Qing He
Journal of System Simulation
Abstract: To solve the traditional Q-learning algorithm for unmanned vehicle path planning suffers from the problems of low planning efficiency and slow convergence speed, for this reason, a path planning algorithm for unmanned delivery vehicles based on the improved Q-learning algorithm is proposed. Learning from the energy iteration principle of the simulated annealing algorithm, adjusts the greedy factor ε to make it change dynamically during the training process, so as to balance the relationship between exploration and utilization, and thus improve the planning efficiency. The reward value in the reward mechanism is changed from a discrete value to a continuous …
Dynamic Path Planning For Mobile Robot Based On Rrt* And Dynamic Window Approach, Rui Zhang, Li Zhou, Zhengyang Liu
Dynamic Path Planning For Mobile Robot Based On Rrt* And Dynamic Window Approach, Rui Zhang, Li Zhou, Zhengyang Liu
Journal of System Simulation
Abstract: A dynamic path planning method combining RRT* and dynamic window approach(DWA) is proposed to realize the obstacle avoidance of mobile robot in complex environment of dynamic obstacles. Improved RRT* algorithm is used to generate the global optimal safe path based on the known environment information. By eliminating the dangerous nodes generated by RRT* algorithm, the security of global path is ensured. Greedy algorithm is used to remove the redundant nodes in the path to reduce the length of global path. DWA is used to track along the global optimal path planned by the improved RRT* algorithm. When static obstacles …
Path Planning Rapid Algorithm Based On Modified Rrt* For Unmanned Surface Vessel, Zhaozhen Jiang, Wenlong Wang, Wenqi Sun
Path Planning Rapid Algorithm Based On Modified Rrt* For Unmanned Surface Vessel, Zhaozhen Jiang, Wenlong Wang, Wenqi Sun
Journal of System Simulation
Abstract: Aiming at the weak purposiveness of rapidly exploring random tree algorithm in USV path planning, a modified rapid algorithm is proposed. The artificial potential field method is improved and the force analysis in four directions is added to comprehensively calculate the resultant force on USV. The calculation method of steering angle is redefined to avoid entering the local optimal trap and can reach the target point smoothly to obtain an initial path. The initial path is used to set the random point sampling area of rapidly exploring random tree algorithm. By reducing the probability of random points generated in …
Path Planning For Improvement Of A* Algorithm And Artificial Potential Field Method, Xiang Yu, Chen Jiang, Sirui Duan, Qianrui Deng
Path Planning For Improvement Of A* Algorithm And Artificial Potential Field Method, Xiang Yu, Chen Jiang, Sirui Duan, Qianrui Deng
Journal of System Simulation
Abstract: A* algorithm has the problem of too many polyline paths and search nodes, while the artificial potential field (APF) method has the problems of local optimality and unattainability. These problems are investigated in this paper. A new hybrid heuristic function is proposed based on the Euclidean distance and projection distance, based on which the A* algorithm process is improved accordingly. The search nodes of the A* algorithm are reduced, and the search efficiency is improved. The optimal node generated by the new A* algorithm is used as the local target point of the APF algorithm to assist in getting …
Urban Uav Path Planning Based On Improved Beetle Search Algorithm, Qingqing Yang, Minyi Deng, Yi Peng
Urban Uav Path Planning Based On Improved Beetle Search Algorithm, Qingqing Yang, Minyi Deng, Yi Peng
Journal of System Simulation
Abstract: An improved SABAS is proposed to improve the safety and path smoothing of UAV missions in urban multi-obstacle environments and to obtain the shortest path. The algorithm no longer completely depends on the difference of odor concentration between the left and the right tentacles of beetle when exploring the path for position update. Instead, it makes full use of the strong searching ability of BAS algorithm, and introduces the annealing algorithm to add the neighborhood position solution of the next position, and finally selects the next best position from the neighborhood position solution. Metropolis criterion of annealing algorithm is …
Path Planning Of Mobile Robots Based On Memristor Reinforcement Learning In Dynamic Environment, Hailan Yang, Yongqiang Qi, Baolei Wu, Dan Rong
Path Planning Of Mobile Robots Based On Memristor Reinforcement Learning In Dynamic Environment, Hailan Yang, Yongqiang Qi, Baolei Wu, Dan Rong
Journal of System Simulation
Abstract: In order to solve the path planning problem of mobile robots in dynamic environment, two-layer path planning algorithm based on improved ant colony algorithm and MA-DQN algorithm is proposed. Static global path planning is accomplished by ant colony algorithm that improved the probabilistic transfer function and the pheromone updating principle; the traditional DQN algorithm structure is improved by using the memristor as the synaptic structure of neural network, and then completed the local dynamic obstacle avoidance of the mobile robot. The path planning mechanism is switched according to whether there are dynamic obstacles within the sensing range of the …
Obstacle Avoidance Path Planning And Simulation Of Mobile Picking Robot Based On Dppo, Junqiang Lin, Hongjun Wang, Xiangjun Zou, Po Zhang, Chengen Li, Yipeng Zhou, Shujie Yao
Obstacle Avoidance Path Planning And Simulation Of Mobile Picking Robot Based On Dppo, Junqiang Lin, Hongjun Wang, Xiangjun Zou, Po Zhang, Chengen Li, Yipeng Zhou, Shujie Yao
Journal of System Simulation
Abstract: Aiming at the autonomous decision-making difficulty of mobile picking robots in random and changeable complicated path environment during field operations, an autonomous obstacle avoidance path planning method based on deep reinforcement learning is propose. By setting the state space and action space and using the artificial potential field method to design the reward function, an obstacle penalty coefficient setting method based on collision cone collision avoidance detection is proposed to improve the autonomous collision avoidance ability. A virtual simulation system is constructed, in which the learning and training of the mobile picking robot is carried out and verified by …
Intelligent Path Planning For Mobile Robots Based On Sac Algorithm, Laiyi Yang, Jing Bi, Haitao Yuan
Intelligent Path Planning For Mobile Robots Based On Sac Algorithm, Laiyi Yang, Jing Bi, Haitao Yuan
Journal of System Simulation
Abstract: Aiming at the high dimension, slow convergence and complex modelling of traditional path planning algorithms for mobile robots, a new intelligent path planning algorithm is proposed, which is based on deep reinforcement learning soft actor-critic (SAC) algorithm to save the poor performance of robot in complicated environments with static and dynamic obstacles. An improved reward function is designed to enable mobile robots to quickly avoid obstacles and reach targets by using state dynamic normalization and priority experience pool techniques. To evaluate the performance, a pygame-based simulation environment is constructed. Compared with proximal policy optimization(PPO) algorithm, experimental …
Simulation Of Real-Time Path Planning And Formation Control For Unmanned Surface Vessel, Dalei Song, Wenhao Gan, Yingzhi Xu, Xiuqing Qu, Jiangli Cao
Simulation Of Real-Time Path Planning And Formation Control For Unmanned Surface Vessel, Dalei Song, Wenhao Gan, Yingzhi Xu, Xiuqing Qu, Jiangli Cao
Journal of System Simulation
Abstract: Safety and collision-free navigation are the basis of normal navigation of an unmanned surface vessel. The high-fidelity virtual ocean is constructed by using Unity3D.On the basis of the vessel modeling, a real-time path planning and formation control method for unknown complex environments is proposed. Firstly, the local environment information is obtained by the laser sensor. Then the real-time local path planning is completed by combining A-star and route-thinning methods under the replanning strategy. In addition, formation control is carried out based on the leader-follower strategy and consistency method, and the artificial potential field …
Obstacle Avoidance And Simulation Of Carrier-Based Aircraft On The Deck Of Aircraft Carrier, Junxiao Xue, Xiangyan Kong, Bowei Dong, Hao Tao, Haiyang Guan, Lei Shi, Mingliang Xu
Obstacle Avoidance And Simulation Of Carrier-Based Aircraft On The Deck Of Aircraft Carrier, Junxiao Xue, Xiangyan Kong, Bowei Dong, Hao Tao, Haiyang Guan, Lei Shi, Mingliang Xu
Journal of System Simulation
Abstract: A predictive depth deterministic policy gradient (PDDPG) algorithm is proposed by combining the least squares method with deep deterministic policy gradient(DDPG) for the problems of strong randomness, poor real-time performance, and slow planning speed by obstacle avoidance on aircraft carrier deck. The short-term trajectory of dynamic obstacles on the deck is predicted by the least square method. DDPG is used to provide agents with the ability to learn and make decisions in continuous space by the short-term trajectory of dynamic obstacles. The reward function is set based on the artificial potential field to improve the convergence speed and accuracy …
Research On Cooperative Path Planning Model Of Multiple Unmanned Vehicles In Real Environment, Guohui Zhang, Xuan Wang, Yanan Zhang, Ang Gao
Research On Cooperative Path Planning Model Of Multiple Unmanned Vehicles In Real Environment, Guohui Zhang, Xuan Wang, Yanan Zhang, Ang Gao
Journal of System Simulation
Abstract: The cluster combat application of unmanned ground vehicles(UVS) is a hot research issue of the intersection of artificial intelligence and battle command. Aiming at the cooperative path planning multiple unmanned vehicles not meeting the dynamic threat condition requirement, by combining the global path planning algorithm A-STAR with the local path planning algorithm RL, from the perspective of perception to behavioral decision making, the cooperative path planning model of multiple unmanned vehicles is studied. The cooperative combat situation threat algorithm, state and action space, reward function and sphere of influence function are designed, the sub-models of formation configuration strategy generation …
Multi-Robot Path Planning Based On Cbs Algorithm, Qiao Qiao, Yan Wang, Zhicheng Ji
Multi-Robot Path Planning Based On Cbs Algorithm, Qiao Qiao, Yan Wang, Zhicheng Ji
Journal of System Simulation
Abstract: Aiming at the long multi-robot planning path and long one-way search running time of conflict-based search(CBS) in the multi-agent path finding(MAPF), an improved CBS algorithm is proposed, which in a two-way A* focus search is used to optimize the search direction and search method. The suboptimal factorωis introduced into the underlying search function of the CBS algorithm to improve the efficiency of path search. The one-way search in the conflict search algorithm is optimized to a two-way A* search. The experimental results show that the path cost of the improved CBS algorithm is shortened …
Particle Swarm Algorithm For Solving Emergency Material Dispatch Considering Urgency, Li Zhang, Huizhen Zhang, Dong Liu, Yuxin Lu
Particle Swarm Algorithm For Solving Emergency Material Dispatch Considering Urgency, Li Zhang, Huizhen Zhang, Dong Liu, Yuxin Lu
Journal of System Simulation
Abstract: In the early stage of major public health events, medical supplies are rapidly consumed and severely insufficient. In order to distribute medical supplies in a reasonable and efficient manner, research on the distribution of emergency medical materials is carried out. The entropy method is introduced to determine the urgency of demand points, thus could give priority to the demand points with high urgency and make the distribution routing as short as possible on that basis to realize the construction of a split delivery and multi-objective emergency medical materials scheduling model based on different urgency of demand points. Meanwhile the …
Simulation Of Multi-Layer Ship Evacuation System Based On Improved A* Algorithm, Dun Meng, Zhuo Hu, Huajun Zhang
Simulation Of Multi-Layer Ship Evacuation System Based On Improved A* Algorithm, Dun Meng, Zhuo Hu, Huajun Zhang
Journal of System Simulation
Abstract: Aiming at the low efficiency of emergency evacuation at sea, an emergency evacuation system based on improved A* algorithm is proposed. Based on the network flow model, the traversal mode of the adjacency node is used to complete the path search, and the influence of the path personnel density and path obstacles is added to the calculation of the cost, which makes the algorithm more practical. In order to improve the efficiency of the algorithm, the node optimization of the network is carried out, and a multi-path optimal scheme is proposed in the case of single layer with multiple …
Research On 3d Path Planning Algorithm Based On Fast Rrt Algorithm, Zhaoqiang Li, Shiyu Zhang
Research On 3d Path Planning Algorithm Based On Fast Rrt Algorithm, Zhaoqiang Li, Shiyu Zhang
Journal of System Simulation
Abstract: RRT (rapidly exploring random tree) algorithm is a sampling-based path planning algorithm, which can search a path in high-dimensional environment. The traditional RRT algorithm has the problems of low node utilization and large amount of calculation. To solve these problems, the fast RRT* (Quick RRT*) algorithm is improved by optimizing the strategy of reselection of parent node and pruning range, improving the sampling method and introducing adaptive step size, which makes the algorithm time-consuming and path length shorter. At the same time, the node connection screening strategy is added to eliminate the excessive turning angle in the path. …
Dqn-Based Path Planning Method And Simulation For Submarine And Warship In Naval Battlefield, Xiaodong Huang, Haitao Yuan, Bi Jing, Liu Tao
Dqn-Based Path Planning Method And Simulation For Submarine And Warship In Naval Battlefield, Xiaodong Huang, Haitao Yuan, Bi Jing, Liu Tao
Journal of System Simulation
Abstract: To realize multi-agent intelligent planning and target tracking in complex naval battlefield environment, the work focuses on agents (submarine or warship), and proposes a simulation method based on reinforcement learning algorithm called Deep Q Network (DQN). Two neural networks with the same structure and different parameters are designed to update real and predicted Q values for the convergence of value functions. An ε-greedy algorithm is proposed to design an action selection mechanism, and a reward function is designed for the naval battlefield environment to increase the update velocity and generalization ability of Learning with Experience Replay (LER). Simulation results …