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5th International Conference on Neural Computing for Advanced Applications (NCAA)

作者： Li, Zijian Yang, Zhiqiang Gao, Huanbing Wang, Xueqiu Shandong Jianzhu Univ Sch Informat & Elect Engn Jinan 250101 Peoples R China Saikesais Biotechnol Co Ltd Jinan Peoples R China

ISBN: (纸本)9789819770038;9789819770045

When applying the rrt algorithm to obstacle avoidance path planning for mobile robots, there are planning efficiency issues such as large search space, long calculation time, and uneven path. This paper proposes an enhanced algorithm that takes map information, starting and ending coordinates as inputs, and outputs an optimized smooth path to address the shortcomings of the original algorithm. This algorithm uses a low-discrepancy Sobol sequence with a probabilistic target bias strategy to optimize the sampling points. Additionally, the concept of target gravity is utilized to adjust the expansion direction of the new nodes, with the gravity coefficient being adaptively adjustable. The original obstacle avoidance path is optimized by pruning optimization removal combined with cubic B-spline curve. In a complex map setting, the improved algorithm demonstrates reductions in running time of 87.71%, 88.59%, and 67.82% compared to rrt, rrt*, and target-biased rrt, respectively. Compared with the other three algorithms, the improved approach reduces the planned path distance by 18.53%, 8.43%, and 15.28%, respectively, demonstrating its efficacy in enhancing path planning efficiency and maintaining path quality.

关键词： Path planning rrt algorithm rrt* algorithm Pruning optimization Target gravity

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Multi-Strategy Improved Rapid Random Expansion Tree (rrt) algorithm for Robotic Arm Path Planning

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2025年第3期16卷 416-423页

作者： Sun, Yuan Zhang, Shoujun Shanghai DianJi Univ Shanghai Peoples R China

The purpose of this paper is to propose an improved rrt algorithm that incorporates multiple improvement strategies to solve the problems of low efficiency, long and unsmooth paths in the traditional rapid random expansion tree (rrt) algorithm for path planning of robotic arms. The algorithm first uses a bidirectional tree extension strategy to generate trees from both the starting point and the target position simultaneously, improving search efficiency and reducing redundant paths. Secondly, the algorithm introduces target bias sampling in combination with local Gaussian sampling, which renders the sampling points more focused on the target area, and dynamically adjusts the distribution to improve sampling efficiency and path connection speed. Concurrently, the algorithm is equipped with an adaptive step size strategy, which dynamically adjusts the expansion step size according to the target distance, thereby achieving a balance between rapid expansion over long distances and precise search at close range. Finally, a collision-free operation is ensured by a path verification mechanism, and the path is smoothed using cubic B-splines and minimum curvature optimisation techniques, significantly improving the smoothness of the path and the feasibility of the robot arm movement. As demonstrated by simulation experiments, the improved rrt algorithm exhibits a reduction in the average path length by 18.15%, planning time by 96.29%, the number of nodes by 92.13%, and the number of iterations by 91.60%, in comparison with the conventional rrt algorithm, when operating in complex map mode. These findings substantiate the efficacy and practicality of the improved rrt algorithm in the domain of robotic arm path planning.

关键词： Robotic arm rrt algorithm path planning target biased sampling Gaussian sampling bidirectional tree extension adaptive step-size

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Cooperative Path Planning for Multiple UAVs Based on APF B-rrt* algorithm

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DRONES 2025年第3期9卷 177-177页

作者： Wu, Cailong Guo, Zhengyu Zhang, Jian Mao, Kai Luo, Delin Xiamen Univ Sch Aerosp Engn Xiamen 361102 Peoples R China Natl Key Lab Air Based Informat Percept & Fus Luoyang 471000 Peoples R China Changji Univ Sch Aeronaut Changji 831100 Peoples R China Naval Aviat Univ Sch Fdn Yantai 264001 Peoples R China

Aiming at the path planning problem of an unmanned aerial vehicle (UAV) in a complex unknown environment, this paper proposes a cooperative path planning algorithm for multiple UAVs. Using the local environment information, several rolling path plannings are carried out by the Artificial Potential Field Bidirectional-Rapidly exploring Random Trees (APF B-rrt*) algorithm. The APF B-rrt* algorithm optimizes the search space by pre-sampling and adapts with an adaptive step while fusing with the APF algorithm for guiding sampling. Then, the generated path is trimmed and smoothed to obtain the optimized path. Then, through the sampling constraint, several paths can be planned at the same time, which are guaranteed not to collide. The model predictive control (MPC) is used to realize the cooperative control of the UAVs, that is, the UAVs reached the destination simultaneously along the planned path. This algorithm achieves some progress in solving the problems of slow convergence speed, an unstable result and an unsmooth path in UAV path planning. Simulation and comparison show that the APF B-rrt* algorithm has certain advantages in algorithm performance.

关键词： cooperative path planning rrt algorithm APF multiple UAVs MPC

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A novel rrt*-Connect algorithm for path planning on robotic arm collision avoidance

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SCIENTIFIC REPORTS 2025年第1期15卷 1-19页

作者： Cao, Miaolong Mao, Huawei Tang, Xiaohui Sun, Yuzhou Chen, Tiandong Zhejiang Univ Sci & Technol Sch Mech & Energy Engn Hangzhou 310023 Peoples R China Zhejiang Ansheng Sci & Technol Stock Co Ltd Jinhua 321300 Peoples R China

To address the limitations of the original algorithm, several optimization techniques are proposed. This article presents an original rrt*-Connect algorithm for the planning of obstacle avoidance paths on robotic arms. These strategies include implementing a target biasing algorithm, using elliptic space sampling to enhance the sampling process, the revision of the cost function to better guide path planning, and implementing an artificial potential field and gradient descent strategy to design adaptive step sizes. Furthermore, the use of segmented B & eacute;zier curves facilitates the generation of a more fluid trajectory when constructing the final path. The effectiveness of these augmentation strategies is corroborated by both simulations and experimental verification on a robotic arm. The simulations showed a 19.39% reduction in average run time and a 5% reduction in average path length compared to the existing rrt*-Connect algorithm. Therefore, The enhanced algorithm meets the requirement for optimal obstacle avoidance path planning by consistently finding the shortest path while avoiding obstacles.

关键词： Robotic arm Path planning rrt algorithm Sampling-based algorithms

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Path Planning for Mobile Robot using Dubins-curve based rrt algorithm with Differential Constraints 61

Path Planning for Mobile Robot using Dubins-curve based RRT ...

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61st International ELMAR Symposium

作者： Zivojevic, Dino Velagic, Jasmin Univ Sarajevo Fac Elect Engn Sarajevo Bosnia & Herceg

ISBN: (纸本)9781728121819

This paper treats a path planning problem for the mobile robot with differential constraints using modified rrt (Rapidly exploring random tree) algorithm based on Dubin's curves. In this paper, the planning problem is considered as a problem of finding a feasible path between the initial and goal point in a static environment with obstacles. Modifications on basic rrt algorithm are necessary due to differential constraints of non-holonomic car-like robot. Dubin's vehicle is selected as robot model, which represents special case of Simple car that moves only forward with constant velocity and can only make left and right turns. algorithm is implemented in ROS (Robot Operating System) and tested through realistic simulations in 2D environment consisted of free space and obstacles. The simulation setup was conducted using a 2D Stage simulator in ROS and RViz tool for visualization. Pioneer 3AT robot model was used as Dubin's car for simulation purposes.

关键词： Path planning rrt algorithm Dubins curves Non-holonomic mobile robot Differential constraints

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An Improved rrt algorithm Based on Heuristic Function Strategy for Manipulator Path Planning 43

An Improved RRT Algorithm Based on Heuristic Function Strate...

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43rd Chinese Control Conference (CCC)

作者： Zuoi, Guoyu Guan, Haishan Zheng, Banggui Beijing Univ Technol Fac Informat Technol Beijing 100124 Peoples R China Beijing Key Lab Comp Intelligence & Intelligent S Beijing 100124 Peoples R China

ISBN: (纸本)9798350366907;9789887581581

Manipulator path planning refers to planning the movement trajectory of a manipulator through algorithms and techniques to realize accurate and efficient operation. It is widely used in industrial production lines, medical surgeries, and other fields. The sampling-based rapid exploration random tree (rrt) algorithm has been widely used in high-dimensional manipulators due to its probabilistic completeness and outstanding expandability. However, the algorithm is purely random in the sampling session, which leads to the existing rrt planning algorithms still having low planning efficiency and poor path quality. To solve these problems, this paper proposes a new and improved method, which assigns a cost value to the sampling points and bases the selection of sampling points on the cost value, so that the growth of the path tree can be oriented to the goal point more quickly. A new evaluation metric, i.e., the average angle of each node in the path, is also designed to evaluate the quality of the path, and the smoother the path is, the more the metric converges to 180 degrees. By comparing our improved rrt algorithm with the original algorithm in several different scenarios, the results show that our improvement possesses shorter running time, shorter path length, and larger average angle of path.

关键词： Path planning rrt algorithm Heuristic function

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Research on stealth route planning based on improved rrt algorithm 5

Research on stealth route planning based on improved RRT alg...

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5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE)

作者： Wang Yang Li Menghan Yang Jun Zhang Chao AVIC First Aircraft Inst Xian Peoples R China Northwest Polytech Univ Xian Peoples R China

ISBN: (纸本)9781665423144

Aiming at the problem of stealth penetration route planning, this article establishes the constraints of route planning firstly, including the maximum turning angle and climbing angle. The objective function is established with the constraints of navigation and radar detection probability. Then the improved rrt algorithm is used to search for way points in 3D space and the route search model can be established. Under the given condition, the simulation analysis is carried out to verify the feasibility to the model.

关键词： stealth penetration route planning radar detection rrt algorithm

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Path Planning of Sand Blasting Robot Based on Improved rrt algorithm 16

Path Planning of Sand Blasting Robot Based on Improved RRT A...

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16th IEEE International Conference on Mechatronics and Automation (IEEE ICMA)

作者： Zhao, Lianyu Liu, Jianpeng Wang, Jutao Tianjin Univ Technol Sch Mech Engn Tianjin Key Lab Adv Mechatron Syst Design & Intel Tianjin 300384 Peoples R China Tianjin Univ Technol Natl Demonstrat Ctr Expt Mech & Elect Engn Educ Tianjin 300384 Peoples R China Tianjin Municipal Key Lab Precis Parts Mfg & Nons Tianjin 300384 Peoples R China

ISBN: (纸本)9781728116976

In order to solve the problem that the sand blasting robot can complete the automatic/semi-automatic blasting in the blasting workshop according to the geometry of the blasting workpiece. This paper proposes a kind of adapt to the traversal of a variety of sandblasting workpieces and path planning methods for obstacle avoidance based on the fast extended random tree (rrt) algorithm. In particular, an improved method for trajectory planning for obstacle avoidance is proposed. Firstly, the sandblasting workpieces are divided into regions and the traversing trajectory planning of the sandblasting area according to the large-scale and diversity characteristics of sandblasting workpieces. Then, the improved rrt algorithm is used to plan the obstacle avoidance trajectory of the simulated traversal trajectory. Through the simulation verification of the method, it is possible to realize a comprehensive, safe, fast and accurate path planning for different blasting workpieces and with faster processing speed than traditional algorithms.

关键词： Sand Blasting Robot Path Planning rrt algorithm

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Using the rrt algorithm to Optimize Classification Systems for Handwritten Digits and Letters 08

Using the RRT Algorithm to Optimize Classification Systems f...

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23rd Annual ACM Symposium on Applied Computing

作者： Radtke, Paulo V. W. Sabourin, Robert Wong, Tony Pontificia Univ Catolica Parana R Imaculada Conceicao 1155 Curitiba Parana Brazil Ecole Technol Super Montreal PQ Canada

ISBN: (纸本)9781595937537

Multi-objective genetic algorithms have been often used to optimize classification systems, but little is discussed on their computational cost to solve such problems. This paper optimizes a classification system with an annealing based approach, the Record-to-Record Travel algorithm. Results obtained are compared to those obtained with a multi-objective genetic algorithm in the same approach. Experiments are performed with isolated handwritten digits and uppercase letters, demonstrating both the effectiveness and lower computational cost of the annealing based approach.

关键词： local search rrt algorithm classification systems ensemble of classifiers

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UAV Path Planning Based on Expert Experience Strategy rrt algorithm 43

UAV Path Planning Based on Expert Experience Strategy RRT Al...

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43rd Chinese Control Conference (CCC)

作者： Zhang, Hengzhuang Wang, Mingming Ping, Yuan Wu, Chong Qi, Juntong Wu, Wenyue Zhou, Enkui Tianjin Univ Sch Elect & Informat Engn Tianjin Key Lab Intelligent Unmanned Swarm Techno Tianjin Peoples R China EFY Intelligent Control Hainan Technol Co Ltd Tianjin 572025 Hainan Peoples R China Shanghai Univ Sch Artif Intelligence Shanghai 200444 Peoples R China

ISBN: (纸本)9798350366907;9789887581581

In response to the issues of node blind expansion, excessive nodes, and frequent acceleration of UAV swarms during path planning using the rrt algorithm, this paper proposes a novel rrt algorithm based on expert experience (E-rrt). Considering the safety and effectiveness of the UAV swarm and its path planning, a strategy involving single UAV reconnaissance and UAV swarm follow-up is adopted. The E-rrt algorithm comprises the following key components: Firstly, an endpoint-guided strategy is devised for the reconnaissance single UAV, introducing a local expansion approach guided by the endpoint to overcome the issue of node blind expansion. After ensuring the reconnaissance single UAV's safety through the reconnaissance path, an expert-based node selection strategy is employed to generate an optimized path for the subsequent UAV swarm follow-up. To enhance the smoothness of the path, a cubic B-spline curve fitting technique is applied to the path generated. Finally, simulations are conducted using Matlab software and the Cyber UAV platform to validate the effectiveness and superiority of the proposed algorithm in UAV swarm path planning.

关键词： rrt algorithm Expert experience UAV swarm Path planning

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