Path planning for UAV based on improved dynamic step RRT algorithm

Xiong, Jing; Duan, Xiaokun

doi:10.1088/1742-6596/1983/1/012034

Cited by 8 publications

(7 citation statements)

References 15 publications

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“…The existing path planning methods can be divided into global path planning [26] and local path planning [27] . Commonly used algorithms include ant colony algorithm [28] , A* algorithm [29] , random number algorithm [30] and greedy algorithm, etc. In this paper, five evaluation indexes that are more important in the medical environment are used as the scoring criteria for the algorithm radar map.…”

Section: Selection Of Path Planning Algorithmmentioning

confidence: 99%

Research on dynamic and static obstacle avoidance strategy and path planning of medical AGV based on the bionic characteristics of antelope migration

Hu,

Niu,

Gao

et al. 2024

Preprint

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Aiming at the problem that Automated guided vehicle (AGV) faces dynamic and static obstacles in the process of transporting patients in medical environment and needs to avoid in real time, inspired by the behavior of antelopes during migration, this paper proposes a bionic obstacle avoidance strategy based on adaptive behavior of antelopes. The artificial potential field and dynamic window algorithm are improved by using the decircling strategy and conical visual distance during antelope migration. The limitations of traditional artificial potential field algorithm are improved by adding new potential field force points into the global planning, and the real-time obstacle avoidance ability of medical AGV is enhanced. The evaluation index of the algorithm is improved in local path planning, and the prediction range of AGV navigation is enlarged. Simulation experiments were carried out through the numerical simulation platform, and the verification results showed that:The bionic obstacle avoidance strategy proposed in this paper can avoid dynamic and static obstacles at the same time. In the example, the success rate of path planning is increased by 34%, the running time is reduced by 33%, and the average path length is reduced by 1%. The proposed method can realize the integration of "dynamic and static" avoidance in the process of transporting patients, and effectively save the time of transporting patients by AGV.It provides a theoretical basis for realizing obstacle avoidance and rapid loading of AGV in medical environment.

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Section: Selection Of Path Planning Algorithmmentioning

confidence: 99%

Research on dynamic and static obstacle avoidance strategy and path planning of medical AGV based on the bionic characteristics of antelope migration

Hu,

Niu,

Gao

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

Section: Selection Of Path Planning Algorithmmentioning

confidence: 99%

Obstacle avoidance strategy and path planning of medical AGV based on the bionic characteristics of antelope migration

Hu,

Niu,

Gao

et al. 2024

Preprint

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Aiming at the problem that Automated guided vehicle (AGV) faces dynamic and static obstacles in the process of transporting patients in medical environment and needs to avoid in real time, inspired by the behavior of antelopes during migration, this paper proposes a bionic obstacle avoidance strategy based on adaptive behavior of antelopes. The traditional artificial potential field and dynamic window algorithm are improved by using the bionic characteristics of antelope migration.By adding new potential field force points and improving the window size, the success rate and prediction range of AGV navigation are improved.Simulation experiments were carried out through the numerical simulation platform, and the verification results showed that:The bionic obstacle avoidance strategy proposed in this paper can avoid dynamic and static obstacles at the same time. In the example, the success rate of path planning is increased by 34%, the running time is reduced by 33%, and the average path length is reduced by 1%. The proposed method can realize the integration of “dynamic and static” avoidance in the process of transporting patients, and effectively save the time of transporting patients by AGV.It provides a theoretical basis for realizing obstacle avoidance and rapid loading of AGV in medical environment.

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“…The RRT algorithm is an intelligent algorithm based on random sampling [8], which has the advantages of fast search and easy implementation. It has excellent performance in path problems in complex environments [9] and has also been well used in robotics [10]. The principle of the RRT algorithm is to obtain random sampling points after giving a starting point to make the tree grow toward the location of the sampling points until the target point is reached, and the tree nodes cannot collide with the danger area, as shown in Figure 1.…”

Section: Rrt Algorithmmentioning

confidence: 99%

Robotic Arms Passing Through Obstacle Nodes: Using an Improved Intelligent Algorithm

2023

IJOMAM

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In the working process, how efficiently the robotic arm passes the obstacle nodes has a great impact on its working efficiency. This paper briefly introduced the rapidly exploring random tree (RRT) algorithm and optimized it with the gravitational potential function based on its shortcomings. The B-spline curve was used to smooth the path. Experimental analyses were carried out in two-dimensional and three-dimensional environments. It was found that the improved RRT algorithm had an average running time of 0.39 s and an average path length of 93.96 mm in the two-dimensional environment; taking environment 1 as an example, the average running time and path length of the improved RRT algorithm was 1.03 s and 147.63 mm, respectively, in the threedimensional environment, after passing through seven path nodes, which were significantly better than the standard RRT algorithm. The results prove the effectiveness of the improved intelligent algorithm for robotic arm path optimization selection. The improved RRT algorithm can be further promoted and applied in practice.

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Path planning for UAV based on improved dynamic step RRT algorithm

Cited by 8 publications

References 15 publications

Research on dynamic and static obstacle avoidance strategy and path planning of medical AGV based on the bionic characteristics of antelope migration

Research on dynamic and static obstacle avoidance strategy and path planning of medical AGV based on the bionic characteristics of antelope migration

Obstacle avoidance strategy and path planning of medical AGV based on the bionic characteristics of antelope migration

Robotic Arms Passing Through Obstacle Nodes: Using an Improved Intelligent Algorithm

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