检索结果-内蒙古大学图书馆

Efficient Sampling-based for Mobile Robot Path Planning in a Dynamic Environment Based on the rapidly-exploring random tree and a Rule-template Sets

引用

INTERNATIONAL JOURNAL OF ENGINEERING 2023年第4期36卷 797-806页

作者： Pohan, M. A. R. Utama, J. Univ Komputer Indonesia Elect Engn Dept Jl Dipatiukur 102-116 Bandung 40132 Indonesia

This study presents an efficient path planning method for mobile robots in a dynamic environment. The method is based on the rapidly-exploring random tree (RRT) algorithm. The two primary processes in mobile robot path planning in a dynamic environment are initial path planning and path re-planning. In order to generate a feasible initial path with fast convergence speed, we used a hybridization of rapidly -exploring random tree star and ant colony systems (RRT-ACS). When an obstacle obstructs the initial path, the path re-planner must be executed. In addition to the RRT-ACS algorithm, we proposed using a rule-template set based on the mobile robot in dynamic environment scenes during the path re-planner process. This novel algorithm is called RRT-ACS with Rule-Template Sets (RRT-ACS+RT). We conducted many benchmark simulations to validate the proposed method in a real dynamic environment. The performance of the proposed method is compared to the state-of-the-art path planning algorithms: RRT*FND and MOD-RRT*. Numerous experimental results demonstrate that the proposed method outperforms other comparison algorithms. The results show that the proposed method is suitable for the use on robots that need to navigate in a dynamic environment, such as self-driving cars.

关键词： Efficient Sampling Path Planning Dynamic Environment rapidly-exploring random tree Rule-template Sets

来源：评论

学校读者我要写书评

暂无评论

Path Planning for Flexible Needle Insertion System Based on Improved rapidly-exploring random tree Algorithm

Path Planning for Flexible Needle Insertion System Based on ...

引用

IEEE International Conference on Information and Automation

作者： Jing Xiong Xia Li Yangzhou Gan Zeyang Xia Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences

ISBN: (纸本)9781467391054

Path planning is one of the most important parts in the research on flexible needle insertion. Based on the Improved rapidly-exploring random tree (I-RRT), the path planning for flexible needle insertion is studied in this paper. Traditional RRT algorithm can generate paths which can avoid obstacle and reach the target precisely, but the path is not continuously differentiable and cannot match the physical constraints of the flexible needle inserting into soft tissue. Aiming at solving this problem, the I-RRT algorithm is proposed to generate paths for minimally invasive treatment and meanwhile guarantee the continuity and effectiveness of the path. The path evaluation function is designed to implement path selection based on path length, obstacle avoidance and the number of arcs. Then the simulation of the flexible needle path is performed in the environment with obstacles. Results show that the I-RRT is more practical and effective for flexible needle insertion path planning.

关键词： Path planning Flexible needle rapidly-exploring random tree

来源：评论

学校读者我要写书评

暂无评论

UAV path planning based on Improved rapidly-exploring random tree

UAV path planning based on Improved Rapidly-exploring Random...

引用

第30届中国控制与决策会议

作者： SUN-Qinpeng LI-Meng WANG-Tianhe ZHAO-Chenpeng College of Electrical Engineering University of Jinan School of Control Science and Engineering Shandong University

The RRT algorithm can be used for path planning of Unmanned Aerial Vehicle（UAV）.However,the efficiency and success rate of the basic RRT algorithm for path planning need to be *** view of this problem,this paper proposed an improved RRT algorithm which based on the dynamic p value and the dynamic step length,and bidirectional RRT（Bi-RRT） is *** effectiveness and advance of the improved RRT algorithm are verified by simulation experiment.

关键词： Unmanned Aerial Vehicle rapidly-exploring random tree Path planning

来源：评论

学校读者我要写书评

暂无评论

Density gradient-RRT: An improved rapidly exploring random tree algorithm for UAV path planning

引用

EXPERT SYSTEMS WITH APPLICATIONS 2024年第PartB期252卷

作者： Huang, Tai Fan, Kuangang Sun, Wen Jiangxi Univ Sci & Technol Sch Mech & Elect Engn Hongqi St 86 Ganzhou Peoples R China Jiangxi Univ Sci & Technol Magnet Suspens Technol Key Lab Jiangxi Prov Hongqi St 86 Ganzhou 341000 Peoples R China Jiangxi Univ Sci & Technol Sch Elect Engn & Automat Hongqi St 86 Ganzhou 34100 Peoples R China

In-depth studies of algorithms for solving motion planning problems have been conducted due to the rapid popularization and development of unmanned aerial vehicles in previous decades. Among them, the classic rapidly exploring random tree (RRT) algorithm has derivative algorithms (e.g., RRT*, Q-RRT*, and F-RRT*) that focus on the optimal path cost of the initial solution. Other improved algorithms, such as RRT-connect and BG-RRT, focus on the optimal time of the initial solution. This article proposes an improved density gradient-RRT (DG-RRT) algorithm based on RRT that improves the efficiency of the guide point and reduces the time lost in the process of obtaining the initial solution through the dynamic gradient sampling strategy. Simultaneously, it reduces the path cost by reconstructing the output path. The proposed algorithm is an expansion algorithm of a random tree, and the performance of the algorithm can be further improved by combining it with other RRT optimization algorithms. DG-RRT and other algorithms are compared in different environments through simulation experiments to verify the advantages of DG-RRT. In addition, it used a set of simulation flight tests to verify the feasibility of the DG-RRT algorithm for UAV path planning.

关键词： Path planning rapidly-exploring random tree Sampling-based algorithms Dynamic density gradient sampling

来源：评论

学校读者我要写书评

暂无评论

A flight-procedure generation framework based on an RRT* path planning algorithm

引用

ADVANCED ENGINEERING INFORMATICS 2025年 64卷

作者： Saez, Raul Toratani, Daichi Mori, Ryota Prats, Xavier Elect Nav Res Inst ENRI Air Traff Management Dept Chofu Tokyo Japan Kobe Univ Grad Sch Maritime Sci Kobe Hyogo Japan Tech Univ Catalonia UPC Dept Phys Aerosp Div Barcelona Spain

We introduce a flight-procedure generation framework that relies on the optimal version of the rapidly- exploring random tree (RRT*) algorithm, where nodes are connected using Dubins paths. This framework is employed for the generation of required navigation performance authorization required approach (RNP AR APCH) procedures, taking into consideration design constraints established by the international civil aviation organization (ICAO). To evaluate the framework's viability, we examine a series of challenging scenarios, for which we swiftly generate a series of operationally-compliant flight procedures. Furthermore, we assess how several of the RRT* configuration parameters can affect the generated procedures. The automation capabilities provided by our framework will benefit flight-procedure designers, saving time in the design process and enabling them to propose flight procedures which will potentially lead to more efficient aircraft trajectories.

关键词： Path planning Required navigation performance Performance based navigation Flight procedure design rapidly-exploring random tree

来源：评论

学校读者我要写书评

暂无评论

A Hierarchical Path Planning Approach Using Waypoint Visibility-Based Target Planner

引用

IEEE ACCESS 2025年 13卷 63627-63639页

作者： Ryu, Hyejeong Kangwon Natl Univ Dept Mechatron Engn Chuncheon Si 24341 South Korea

This paper presents a hierarchical path planning framework for efficient and practical robot navigation in environments with unknown obstacles that are not registered in a given map. While existing path planning approaches primarily focus on separately enhancing the performance of either the local or global planner, we propose a novel framework that employs a target planner to integrate the two, enabling adaptive navigation toward the final goal position via reachable waypoints. The proposed framework integrates a visibility-based target planner to dynamically evaluate the distance and heading visibility of the current target waypoint along a global path computed by the global planner. By dynamically assessing visibility, the visibility-based target planner autonomously updates the robot's target waypoint if the current waypoint becomes unreachable owing to obstacles, thereby ensuring that the local planner efficiently navigates the robot to the updated target. Experiments were conducted to validate the proposed framework against a conventional sequential waypoint assignment approach. The results demonstrate that, compared to the conventional approach, the hierarchical framework using the visibility-based target planner reduces the overall navigation time by 49.6 % and 52.6 % in two different experiments while requiring fewer control commands. These improvements indicate that the proposed framework effectively minimized unnecessary detours and enabled the robot to reach the final goal position more efficiently, even in the presence of unmapped obstacles.

关键词： Robots Navigation Real-time systems Path planning Heuristic algorithms Robot sensing systems Trajectory Costs Collision avoidance Vehicle dynamics Mobile robots navigation path planning nearness diagram rapidly-exploring random tree

来源：评论

学校读者我要写书评

暂无评论

Sobol sequence RRT* and numerical optimal joint algorithm-based automatic parking trajectory planning of four-wheel steering vehicles

引用

ROBOTICS AND AUTONOMOUS SYSTEMS 2025年 186卷

作者： Yang, Jiulong Wang, Junnian Li, Jiajun Meng, Xiangzhe Jiang, Xingwei Lu, Changgang Jilin Univ Natl Key Lab Automot Chassis Integrat & B Renmin St 5988 Changchun Peoples R China China FAW Grp Co Ltd Intelligent Connected Vehicle Dev Inst Changchun Peoples R China

Four-wheel steering can effectively improve turning agility and mitigate parking spatial requirement. Addressing the issues of low sampling point quality and poor efficiency in existing rapidly-exploring random tree (RRT) and its improved algorithms for automatic parking assist (APA) system, a parking trajectory planning algorithm combining Sobol-RRT* with Reeds-Shepp curve and numerical optimal control within four-wheel steering kinematic model constraints is proposed in this paper to improve parking space utilization rate, cope with dynamic obstacles during parking process. First, the hierarchical framework of the proposed path planning algorithm is introduced, which is used as the basis of the planning algorithm, and the kinematics model of the four-wheel steering vehicle is established. Second, the pseudo-random sequences of RRT algorithm are replaced by Sobol sequences with uniform difference characteristics. Then, the parking trajectory planning problem is formulated with consideration of the system dynamic equation constraints based on the four-wheel steering kinematics model and the dynamic obstacle constraints based on the "triangular area method". Finally, the planned parking trajectory for the four-wheel steering vehicle is obtained by solving the optimal control problem and cubic spline curve fitting. Simulation in typical parking conditions validated the proposed planning algorithm on improvement of the APA system adaptability to challenging parking environment with dynamic obstacles.

关键词： Automatic parking Four-wheel steering Path planning rapidly-exploring random tree Numerical optimal control Dynamic obstacle

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

IQ-RRT*: a path planning algorithm based on informed-RRT* and quick-RRT

引用

INTERNATIONAL JOURNAL OF COMPUTATIONAL SCIENCE AND ENGINEERING 2025年第3期28卷 303-313页

作者： Rahman, Afroze Kundu, Anindita Banerjee, Sumanta Heritage Inst Technol Dept Comp Sci & Engn Kolkata 700107 India Vellore Inst Technol Sch Comp Sci & Engn SCOPE Dept Software Syst Vellore 632014 India Heritage Inst Technol Dept Mech Engn Kolkata 700107 India

Optimal path planning algorithms such as the RRT* and its variants seek to generate the best feasible path from an initial state to a goal state in the least possible time. Prior work on RRT* has focused on improving the convergence rate of the algorithm while keeping its computational complexity unchanged. Informed-RRT* and quick-RRT* are two such variants that, in certain scenarios, converge to the optimal path faster than RRT* does. This work focuses on the novel addition of informed sampling to quick-RRT* to enhance its convergence rate. The resultant algorithm provides initial solutions with costs comparable to quick-RRT* and convergence rates at par with quick-RRT* in the worst case. The authors have concluded that this new algorithm, named IQ-RRT*, outperforms informed-RRT* and quick-RRT* in a multitude of scenarios. IQ-RRT*, unlike quick-RRT*, is a faster alternative to informed-RRT* even in cluttered environments and mazes with long corridors.

关键词： path planning informed sampling fast convergence rapidly-exploring random tree RRT

来源：评论

学校读者我要写书评

暂无评论

Real-Time Path Planning Under Signal Temporal Logic Specifications in Dynamic Environment 17th

Real-Time Path Planning Under Signal Temporal Logic Specific...

引用

17th International Conference on Intelligent Robotics and Applications

作者： Zhang, Hao Yang, Yan Zhang, Yunxu Cao, Baiheng Tian, Chang Univ Sci & Technol Beijing Sch Intelligence Sci & Technol Beijing 100083 Peoples R China Univ Sci & Technol Beijing Key Lab Intelligent Bion Unmanned Syst Minist Educ Beijing 100083 Peoples R China

ISBN: (纸本)9789819607884;9789819607891

Path planning is an important branch in the field of robotics, and the use of Signal Temporal Logic (STL) to solve planning problems is currently a very hot research topic. STL, as a logic language for describing task specifications and executes them, can express various spatiotemporal constraints. Its semantic robustness is used to analyze systems over a certain continuous time, by proposing corresponding robust functions to quantify the degree to which a system satisfies or violates the STL specifications. In the environment with dynamic and static obstacles, based on the Real-Time rapidly-Exploration random tree (RT-RRT*) planning algorithm, a robust function based on STL and a smoothing function are proposed to maximize the system's robustness and smoothness, thereby finding the optimal solution. Simulation results indicate that this method can compute and compare multiple cost values to select the most robust planning path, satisfying the STL specifications.

关键词： Signal Temporal Logic rapidly-exploring random tree Dynamic Path Planning

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：