检索结果-内蒙古大学图书馆

Path planning for autonomous vehicles under multi-road condition based on improved artificial potential field with A* algorithm

引用

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING 2025年

作者： Wu, Zhi Liu, Fang Zhou, Jiacheng Fan, Fei Wang, Zhen Wuhan Text Univ Sch Mech Engn & Automat 1 Text Rd Wuhan 430073 Hubei Peoples R China Wuhan Text Univ Hubei Key Lab Digital Text Equipment Wuhan Peoples R China Wuhan Univ Hubei Key Lab Elect Mfg & Packaging Integrat Wuhan Peoples R China Liaoning Tech Univ Min Hydraul Technol & Equipment Engn Res Ctr Fuxin Peoples R China

Path planning for autonomous vehicles is a key technology in the field of intelligent transportation. In this paper, an improved artificial potential field (APF) with A* algorithm is proposed for dynamic path planning of autonomous vehicles under multi-road conditions. Firstly, for the defects of APF algorithm, distance impact factor to the target and minimum gravitational value are respectively added for the APF potential field. Moreover, vehicle obstacle avoidance and lane-changing are realized by combining APF with Safety Distance Model (SDM-APF). Secondly, the heuristic function of the A* algorithm is improved to reduce redundant path points and enhance planning efficiency. The improved A* algorithm is integrated with the SDM-APF algorithm to further improve path planning performance. Finally, a traffic map of a multi-road scenario is designed for simulation using graphical user interface. The simulation results demonstrate that the improved A* algorithm outperforms the traditional approach, achieving a 2.5% reduction in redundant points and a 9.2% decrease in average intersection angles, along with a 2.0% increase in planning efficiency. The improved SDM-APF algorithm also demonstrates exceptional lane-centering capability and target accessibility, exhibiting almost 0 path volatility. From the initial point to the destination, even if the road conditions are varied and complex, the hybrid A*-SDM-APF algorithm can still successfully reach the destination, and ensure safety, smoothness, and stability of the vehicle trajectories. The simulation results provide strong evidence for the effectiveness and superiority of the algorithmic improvements and combinations.

关键词： Autonomous vehicles dynamic path planning lane-changing decision artificial potential field algorithm safe distance model A* algorithm

来源：评论

学校读者我要写书评

暂无评论

Optimized artificial potential field algorithm to multi-unmanned aerial vehicle coordinated trajectory planning and collision avoidance in three-dimensional environment

引用

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART G-JOURNAL OF AEROSPACE ENGINEERING 2019年第16期233卷 6032-6043页

作者： Tang, Jun Sun, Jiayi Lu, Cong Lao, Songyang Univ Autonoma Barcelona Dept Telecommun & Syst Engn Carrer Dels Emprius 2 Sabadell 08202 Barcelona Spain Natl Univ Def Technol Coll Syst Engn Changsha Hunan Peoples R China

Multi-unmanned aerial vehicle trajectory planning is one of the most complex global optimum problems in multi-unmanned aerial vehicle coordinated control. Results of recent research works on trajectory planning reveal persisting theoretical and practical problems. To mitigate them, this paper proposes a novel optimized artificial potential field algorithm for multi-unmanned aerial vehicle operations in a three-dimensional dynamic space. For all purposes, this study considers the unmanned aerial vehicles and obstacles as spheres and cylinders with negative electricity, respectively, while the targets are considered spheres with positive electricity. However, the conventional artificial potential field algorithm is restricted to a single unmanned aerial vehicle trajectory planning in two-dimensional space and usually fails to ensure collision avoidance. To deal with this challenge, we propose a method with a distance factor and jump strategy to resolve common problems such as unreachable targets and ensure that the unmanned aerial vehicle does not collide into the obstacles. The method takes companion unmanned aerial vehicles as the dynamic obstacles to realize collaborative trajectory planning. Besides, the method solves jitter problems using the dynamic step adjustment method and climb strategy. It is validated in quantitative test simulation models and reasonable results are generated for a three-dimensional simulated urban environment.

关键词： Multi-unmanned aerial vehicle 3D trajectory planning collision avoidance artificial potential field algorithm

来源：评论

学校读者我要写书评

暂无评论

Collision-free Path Planning for UAVs using Efficient artificial potential field algorithm 93

Collision-free Path Planning for UAVs using Efficient Artifi...

引用

IEEE 93rd Vehicular Technology Conference (VTC-Spring)

作者： Selvam, Praveen Kumar Raja, Gunasekaran Rajagopal, Vasantharaj Dev, Kapal Knorr, Sebastian Ernst Abbe Univ Dept SciTech Jena Germany Ernst Abbe Univ Dept Elect & Comp Engn Jena Germany Anna Univ Dept Comp Technol Chennai Tamil Nadu India Anna Univ Dept Aerosp Engn Chennai Tamil Nadu India Trinity Coll Dublin CONNECT Ctr Dublin Ireland

ISBN: (纸本)9781728189642

Unmanned Aerial Vehicles (UAVs), a new emerging form of Internet of Things (IoT), is a promising technology to be widely used in both civil and military applications. On the fly, the UAVs need to find an efficient and safe path by avoiding both static and dynamic obstacles to carry out any mission successfully. The artificial potential field (APF) algorithm is one of the conventional catalysts in UAV path planning. However, APF-aided UAVs can be easily trapped into a local minimum solution before reaching the destination. Therefore, this paper proposes an efficient APF algorithm for Collision-free Path Planning (eAPF-CPP) in UAVs. In eAPF-CPP, the attractive and repulsive potentials evaluate the quadratic distance to the destination and the obstacle respectively. The evaluation aids the UAV to select the optimal path in navigation. The eAPF-CPP mechanism is simulated in the Software-In-The-Loop (SITL) setup, and the experimental results show that the eAPF-CPP mechanism utilizes an average of 24.4 seconds to track a safe path and has a lower collision rate of 8.56% compared with Artifical potential field Approach (APFA).

关键词： Unmanned Aerial Vehicle (UAV) Obstacle Avoidance Software-In-The-Loop (SITL) artificial potential field algorithm Collision-free Path Planning

来源：评论

学校读者我要写书评

暂无评论

A path planning approach for unmanned surface vehicles based on improved artificial potential field algorithm and COLREGS 43

A path planning approach for unmanned surface vehicles based...

引用

43rd Chinese Control Conference (CCC)

作者： Li, Jing Wan, Lili Wuhan Polytech Univ Sch Elect & Elect Engn Wuhan 430023 Peoples R China

ISBN: (纸本)9798350366907;9789887581581

Path planning is a core issue of autonomous navigation for unmanned surface vehicles (USVs). To guarantee navigation safety, this paper proposes an Improved artificial potential field (IAPF) algorithm for path planning of USVs. On the one hand, to solve the local optimal problem of artificial potential field (APF) algorithm, an adjustment factor is introduced in the repulsive potential field function. On the other hand, to ensure the collision avoidance safety in complex encounter scenarios, the International Regulations for Preventing Collisions at Sea (COLREGS) is utilized in the IAPF algorithm. The simulation experiments verify that the path planned via the IAPF algorithm is safer and more efficient than APF algorithm.

关键词： artificial potential field algorithm COLREGS Path planning USV

来源：评论

学校读者我要写书评

暂无评论

A path planning approach for unmanned surface vehicles based on improved artificial potential field algorithm and COLREGS

A path planning approach for unmanned surface vehicles based...

引用

第43届中国控制会议

作者： Jing Li Lili Wan School of Electrical and Electronic Engineering Wuhan Polytechnic University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Path planning is a core issue of autonomous navigation for unmanned surface vehicles(USVs). To guarantee navigation safety, this paper proposes an Improved artificial potential field(IAPF) algorithm for path planning of USVs. On the one hand, to solve the local optimal problem of artificial potential field(APF) algorithm, an adjustment factor is introduced in the repulsive potential field function. On the other hand, to ensure the collision avoidance safety in complex encounter scenarios, the International Regulations for Preventing Collisions at Sea(COLREGS) is utilized in the IAPF algorithm. The simulation experiments verify that the path planned via the IAPF algorithm is safer and more efficient than APF algorithm.

关键词： artificial potential field algorithm COLREGS Path planning USV

来源：评论

学校读者我要写书评

暂无评论

Safe artificial potential field-Novel Local Path Planning algorithm Maintaining Safe Distance From Obstacles

引用

IEEE ROBOTICS AND AUTOMATION LETTERS 2023年第8期8卷 4823-4830页

作者： Szczepanski, R. Nicolaus Copernicus Univ Inst Engn & Technol Fac Phys Astron & Informat PL-87100 Torun Poland

This letter proposes a novel local path planning algorithm called Safe artificial potential field (SAPF). The algorithm uses the attractive potential for goal reaching as the original one. However, the repulsive potential is replaced by a general obstacle potential, equal to repulsive potential, vortex potential, or their superposition. Moreover, the analytical tuning procedure of SAPF is described in this letter. The proposed algorithm has been compared to the original artificial potential field (APF), Vortex APF (VAPF), and Dynamic Window Approach (DWA). The comparison has been provided using both, simulational and experimental validation. The SAPF allows to avoid simple local minima, keep safety distance from obstacles and move through narrow corridors. The obtained results in the form of videos are attached as supplementary files.

关键词： Path planning Heuristic algorithms Vehicle dynamics Prediction algorithms Collision avoidance Safety Optimization Path planning problem artificial potential field algorithm mobile robot autonomous vehicle safe distance

来源：评论

学校读者我要写书评

暂无评论

Local Path Planning algorithm Based On artificial potential field With Adaptive Scaling Factor 28

Local Path Planning Algorithm Based On Artificial Potential ...

引用

28th International Conference on Methods and Models in Automation and Robotics (MMAR)

作者： Szczepanski, Rafal Gul, Faiza Nicolaus Copernicus Univ Torun Fac Phys Astron & Informat Inst Engn & Technol Torun Poland Air Univ Dept Elect Engn Aerosp & Aviat Campus Kamra Pakistan

ISBN: (纸本)9798350362350;9798350362343

The paper presents an adaptive local path planner based on the artificial potential field algorithm and the Widrow-Hoff rule. The proposed algorithm maintains the required distance from obstacles. The limitation of the scaling factor of repulsive potential allows for proper continuous operation. It provides smooth, collision-free, and goal-reaching operation of mobile robots. The impact of adaptation gain and the required distance from obstacles on robot movement have been examined in randomly generated environments.

关键词： local path planning mobile robot artificial potential field algorithm adaptive control Widrow-Hoff rule

来源：评论

学校读者我要写书评

暂无评论

Obstacle Avoidance Strategy and Path Planning of Medical Automated Guided Vehicles Based on the Bionic Characteristics of Antelope Migration

引用

BIOMIMETICS 2025年第3期10卷 142-142页

作者： Hu, Jing Niu, Junchao Zhang, Bangcheng Gao, Xiang Zhang, Xinming Huang, Sa Changchun Univ Sci & Technol Sch Mechatron Engn Changchun 130022 Peoples R China Changchun Inst Technol Changchun 130103 Peoples R China Foshan Univ Sch Mechatron Engn & Automat Foshan 528225 Peoples R China Guangdong Educ Dept Precis Machining & Special Machining Innovat Team Foshan 528225 Peoples R China Jilin Univ Bethune Clin Sch Med 2 Changchun 130015 Peoples R China

Automated Guided Vehicles (AGVs) face dynamic and static obstacles in the process of transporting patients in medical environments, and they need to avoid these obstacles in real time. This paper proposes a bionic obstacle avoidance strategy based on the adaptive behavior of antelopes, aiming to address this problem. Firstly, the traditional artificial potential field and dynamic window algorithm are improved by using the bionic characteristics of antelope migration. Secondly, the success rate and prediction range of AGV navigation are improved by adding new potential field force points and increasing the window size. Simulation experiments were carried out on a 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 help realize the integration of "dynamic and static" avoidance in the process of transporting patients and effectively save time by using AGVs to transport patients. It provides a theoretical basis for realizing obstacle avoidance and rapidly loading AGVs in medical environments.

关键词： medical AGV bionic strategy artificial potential field algorithm dynamic window algorithm path planning

来源：评论

学校读者我要写书评

暂无评论

Intelligent decision making algorithm for path planning based on reference Linguistic Fuzzy set

引用

JOURNAL OF SUPERCOMPUTING 2025年第1期81卷 1-23页

作者： Gan, Lian Du, Yuhong Wang, Shuai Ren, Weijia Rong, Ziqi Li, Xinlong Tiangong Univ Sch Mech Engn Tianjin 300387 Peoples R China Tianjin Univ Sci & Technol Coll Mech Engn Tianjin 300222 Peoples R China

This paper proposes a novel path planning algorithm called Reference Linguistic Fuzzy algorithm (RLFA);moreover, the parametric analysis procedure of the RLFA is described in this paper. It finds the optimal path by calculating the decision value required by path planning. However, most of the research ignores the issue of equal decision scores. The proposed algorithm has been compared to the original distance metrics, the fuzzy synthetic evaluation method, the modified three-way TOPSIS method, and the Generalized TODIM method. Compared with the existing algorithms, the algorithm proposed in this paper improves the reliability of path planning decision making and eliminates the defects of the traditional algorithms, which rely on parameter settings. It combines subjective and objective dual evaluation perspectives to correct the possible bias in the single subjective perspective. This paper is supported by experimental validation, and the results show that the proposed algorithm can achieve the optimal solution under all conditions.

关键词： Path planning artificial potential field algorithm Mobile robot Fuzzy linguistic term set Decision making

来源：评论

学校读者我要写书评

暂无评论

Hybrid path planning for USV with kinematic constraints and COLREGS based on APF-RRT and DWA

引用

OCEAN ENGINEERING 2025年 318卷

作者： Wang, Yuchao Li, Jialing Zhao, Shiquan Su, Peng Fu, Huixuan Niu, Hongmin Harbin Engn Univ Coll Intelligent Syst Sci & Engn Harbin 150001 Peoples R China China Ship Res & Design Ctr Wuhan 430060 Peoples R China Changan Univ Sch Elect & Control Engn Xian 710064 Peoples R China

Intelligent algorithms are increasingly employed to optimize the ship path planning, ensuring safe navigation and preventing potential collisions. This paper proposes a hybrid path planning approach that incorporates kinematic constraints, which includes both global and local path planning. Firstly, the artificial potential field (APF) is utilized to guide node growth, allowing the Rapidly-exploring Random Tree (RRT) to more efficiently navigate through multi-obstacle areas. To enhance the robustness of the algorithm, the gravitational coefficient optimization method and dynamic step-size strategy are introduced. Additionally, a novel RRT termination method is proposed to accelerate search speed by either using the node that satisfies the termination criteria as the last path point or by inserting anew node to fulfill all constraints. Furthermore, building upon the Dynamic Window algorithm (DWA), a turning function based on maritime rules and the Collision Risk Index (CRI) are incorporated. New cost functions are established accordingly for different types of obstacles. The results from simulation experiments demonstrate the superior performance of the proposed method. The enhanced global path planning algorithm improves the efficiency of global path acquisition in diverse environments. Moreover, the proposed local path planning algorithm can accurately assess and respond to different scenarios and performs better than the traditional method in collision avoidance.

关键词： Unmanned surface vehicle Rapidly-exploring random tree artificial potential field algorithm Dynamic window algorithm Collision avoidance COLREGS

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：