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P-19.2: A Review of path planning algorithms for Automated Driving Vehicles

SID Symposium Digest of Technical Papers 2024年第S1期55卷 1564-1567页

作者： Yu Zhang Wanlin Li North China University of Technology Beijing China

With the continuous development of automated driving, the path planning algorithm of unmanned vehicles has been continuously innovated. First, some basic concepts of path planning are briefly introduced. Secondly, starting with the classification idea of path planning algorithm based on graph structure and sampling, the paper introduces four typical basic algorithms: Dijkstra algorithm, A* algorithm, PRM algorithm and RRT algorithm. In addition, the Apollo algorithm, which has been studied most at present, is also introduced. The principle and application scenario of each algorithm are summarized. Finally, several new algorithms and their development prospects are introduced.

关键词： path planning algorithm the Apollo algorithm

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path planning Trends for Autonomous Mobile Robot Navigation: A Review

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SENSORS 2025年第4期25卷 1206-1206页

作者： Tang, Yuexia Zakaria, Muhammad Aizzat Younas, Maryam Univ Malaysia Pahang Al Sultan Abdullah Fac Mfg & Mechatron Engn Technol Pekan 26600 Pahang Malaysia Nanning Univ Intelligent Mfg Coll Nanning 530299 Peoples R China Univ Malaysia Pahang Al Sultan Abdullah Ctr Automot Engn Autonomous Vehicle Lab Pekan 26600 Pahang Malaysia Univ Malaysia Pahang Al Sultan Abdullah Ctr Adv Ind Technol Pekan 26600 Pahang Malaysia

With the development of robotics technology, there is a growing demand for robots to perform path planning autonomously. Therefore, rapidly and safely planning travel routes has become an important research direction for autonomous mobile robots. This paper elaborates on traditional path-planning algorithms and the limitations of these algorithms in practical applications. Meanwhile, in response to these limitations, it reviews the current research status of recent improvements to these traditional algorithms. The results indicate that these improved path-planning algorithms perform well in tests or practical applications, and multi-algorithm fusion for path planning outperforms single-algorithm path planning.

关键词： autonomous driving path planning algorithm global path planning local path planning intelligent planning algorithm

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A practical path planning and navigation algorithm for an unmanned surface vehicle using the fast marching algorithm

A practical path planning and navigation algorithm for an un...

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Oceans 2015 Genova

作者： Liu, Yuanchang Song, Rui Bucknall, Richard UCL Dept Mech Engn London WC1E 7JE England

ISBN: (纸本)9781479987375

There has been an increasing interest in the development of unmanned surface vehicles (USVs) in recent decades. As USVs are required to carry out complex missions without any human intervention in various environments, an intelligent path planning algorithm is critical. A path planning algorithm is able to utilise environment data to calculate an optimal trajectory to guarantee safety. To achieve this, in this paper, a novel path planning and navigation (PN) algorithm is proposed. The PN algorithm uses the fast marching method (FMM) as the base algorithm to search for an optimal collision-free trajectory. Then, to facilitate the trajectory tracking of the USV, a new waypoint-generator based on the line-of-sight (LOS) is developed to generate the optimal number of waypoints from the path. The proposed algorithm has been evaluated based on the Springer USV, and has been shown that it can be seamlessly integrated with the Springer's exiting autopilot to achieve full autonomy.

关键词： unmanned surface vehicle (USV) path planning algorithm USV dynamics waypoint tracking

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A study on real-time path planning method for skin machining based on frame feature extraction and chronological feature optimization

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CIRP JOURNAL OF MANUFACTURING SCIENCE AND TECHNOLOGY 2024年 51卷 145-160页

作者： Liu, Chang Wang, Xiaoyao Du, Fuzhou Beihang Univ Sch Mech Engn & Automat Beijing 100191 Peoples R China

Skin, as the crucial component of aircraft, should be milled along the edges of the frame to ensure the mounting accuracy. Traditional skin milling uses visual measurement and offline planning to generate a machining path that corresponds to the overall shape of the frame edge. To enhance adaptability and processing efficiency, an online planning method is proposed. However, it imposes greater demands on the computational efficiency, accuracy, and stability of the algorithm. In this paper, a real-time path planning method based on frame feature extraction and chronological feature optimization is proposed for the milling of attached frame-skin. The method uses a line laser to scan the surface features of both skin and frame structures, facilitating real-time extraction of feature structures. Periodic calculations of position and posture are conducted based on the time series, and a non-fitting method is used to generate a smooth and high-precision machining trajectory. The efficacy in achieving real-time path planning for the milling module is verified by experiments on prototypes of aircraft skin. The algorithm exhibits a duration of less than 8 ms in a run cycle, while maintaining accuracy within +/- 0.5mm.

关键词： path planning algorithm Aircraft skin machining Frame feature extraction Chronological feature optimization

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Optimizing floor plans of accessible restrooms in elderly long-term care facilities: a path planning approach

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ARCHITECTURAL ENGINEERING AND DESIGN MANAGEMENT 2024年第4期20卷 891-910页

作者： Yuan, Hao Shen, Xiumei Southeast Univ Nanjing Jiangsu Peoples R China Southeast Univ Sch Architecture Nanjing 210019 Jiangsu Peoples R China

Navigating narrow restrooms is challenging for the elderly using wheelchairs or walkers (EUWW). Existing research focuses on the convenience of furniture use in the restroom and overlooks the convenience of mobility between furniture pieces. However, the floor plans of accessible restrooms determine the mobility path of EUWW, affecting mobility convenience. Thus, to improve mobility, floor plans should be evaluated to shorten movement distances and reduce bends. Experiments in constructed environments were expensive. This study instead proposes a novel path-planning based method for accessible restroom floor plan evaluation, simulating mobility paths in a virtual environment, and evaluating how the floor plans of accessible restrooms affect mobility and convenience. The results showed that: (1) wheelchair users, who approach the toilet from the rear, and walker users find opposite wall toilet-sink arrangements convenient. While Wheelchair users, who approach the toilet from the side or front, find it convenient if the toilet and sink are situated on different walls at a 90 degrees angle. Toilets and sinks on the same wall are inconvenient. (2) Corner sinks and toilets reduce EUWW's turning angles. (3) The farther the sink is from the side wall, the more convenient it is for EUWW. (4) The 45 degrees side approach is the most convenient for moving, followed by the frontal approach, and lastly the 90 degrees approach. Theoretically, this study uses path planning algorithms, simulating the movement of EUWW with varying capabilities and offering a new perspective for barrier-free architectural design. Practically, this study provides recommendations for optimizing accessible restroom floor plans.

关键词： Accessible restroom floor plan optimization mobility convenience path planning algorithm wheelchair and walker users

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A Novel Goal-oriented Sampling Method for Improving the Convergence Rate of Sampling-based path planning for Autonomous Mobile Robot Navigation

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DEFENCE SCIENCE JOURNAL 2023年第3期73卷 322-331页

作者： Ganesan, Sivasankar Natarajan, Senthil Kumar Thondiyath, Asokan Mepco Schlenk Engn Coll Sivakasi 626005 Tamil Nadu India Indian Inst Technol Madras Chennai 600036 Tamil Nadu India

Autonomous Mobile Robots' performance relies on intelligent motion planning algorithms. In autonomous mobile robots, sampling-based path-planning algorithms are widely used. One of the efficient sampling-based path planning algorithms is the Rapidly Exploring Random Tree (RRT). However, the solution provided by RRT is suboptimal. An RRT extension known as RRT* is optimal, but it takes time to converge. To improve the RRT* slow convergence problem, a goal-oriented sampling-based RRT* algorithm known as GS-RRT* is proposed in this paper. The focus of the proposed research work is to reduce unwanted sample exploration and solve the slow convergence problem of RRT* by taking more samples in the vicinity of the goal region. The proposed research work is validated in three different environments with a map size of 384*384 and compared to the existing algorithms: RRT, Goal-directed RRT(G-RRT), RRT*, and Informed-RRT*. The proposed research work is compared with existing algorithms using four metrics: path length, time to find the solution, the number of nodes visited, and the convergence rate. The validation is done in the Gazebo Simulation and on a TurtleBot3 mobile robot using the Robotics Operating System (ROS). The numerical findings show that the proposed research work improves the convergence rate by an average of 33 % over RRT* and 27 % over Informed RRT*, and the node exploration is 26 % better than RRT* and 20% better than Informed RRT*.

关键词： Goal-oriented sampling Mobile robot navigation path planning algorithm Rapidly exploring random tree

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Dynamic path planning algorithms With Load Balancing Based on Data Prediction for Smart Transportation Systems

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IEEE ACCESS 2020年 8卷 15907-15922页

作者： Sun, Ning Shi, Huizhu Han, Guangjie Wang, Bin Shu, Lei Hohai Univ Coll Internet Things Engn Changzhou 213022 Jiangsu Peoples R China Nanjing Agr Univ Coll Engn Nanjing 210095 Peoples R China Hohai Univ Coll Informat & Commun Syst Changzhou 213022 Jiangsu Peoples R China Univ Lincoln Sch Engn Lincoln LN6 7TS England

In modern transportation, traffic congestion has become an urgent problem in large and medium-sized cities. In smart transportation systems, it is an effective solution to design load balancing path planning algorithms that can dynamically adapt to traffic conditions in order to avoid congestion. In this work, a traffic path planning algorithm based on data prediction (TPPDP) is proposed to find the path with the shortest travel time, which is built on a predictive model based on historical traffic data and current traffic information. Furthermore, a path planning algorithm based on data prediction with load balancing (TPPDP-LB) is also proposed, which combines the predicted information and the number of concurrent requests to achieve the path with shortest travel time while maintaining global load balancing. A specific distributed computing framework for TPPDP-LB algorithm is designed to reduce the runtime of the algorithm. The simulation results proved that both TPPDP and TPPDP-LB algorithms have the advantage of shortest travel time, and TPPDP-LB algorithm achieves load balancing of computing. It is also proved that the distributed computing framework designed for TPPDP-LP algorithm can effectively reduce the runtime of system as well as keep the accuracy of algorithm.

关键词： path planning algorithm data prediction load balancing distributed computing smart transportation

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Analysis and Evaluation of path planning algorithms for Autonomous Driving of Electromagnetically Actuated Microrobot

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INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS 2020年第11期18卷 2943-2954页

作者： Lim, Seung-hyun Sohn, Sun Woo Lee, Hyoryong Choi, Donghyeon Jang, Eunsil Kim, Minhye Lee, Junhyeong Park, Sukho Daegu Gyeongbuk Inst Sci & Technol DGIST Sch Undergrad Studies Daegu 42988 South Korea Daegu Gyeongbuk Inst Sci & Technol DGIST Dept Robot Engn Daegu 42988 South Korea

In order to overcome the limitations of the A* algorithm in the autonomous control of electromagnetically actuated microrobots, this study introduces three modified path planning algorithms (A*-WAPP, A*-waypoints, A*-WAPP-waypoints) using the concept of Wall Avoiding path planning (WAPP) and waypoints. Through the autonomous driving experiment of an electromagnetically actuated microrobot, the three modified path planning algorithms based on A* and the original A* algorithm were evaluated using four performance measures. As a result, it was confirmed whether significant changes exist between the A* algorithm and the A*-based modified algorithms about the fitness for the autonomous driving environment of the electromagnetically actuated microrobot. First, compared to the path of the A* algorithm, A*-WAPP algorithm generated a stable path that dramatically reduced the collision between the microrobot and the obstacle. However, in the autonomous driving of the microrobot, A*-WAPP algorithm increased the driving distance and driving time. On the other hand, A*-waypoints algorithm showed a tendency in reducing the driving distance and driving time of the autonomous driving microrobot by simplifying the generated path, but still showed the collision problem between the microrobot and the obstacle. Finally, the path generated by the A*-WAPP-waypoints algorithm greatly increased the stability of the autonomous driving microrobot and showed great advantages of the decreases in the driving distance and driving time. In conclusion, it was confirmed that the proposed A*-WAPP-waypoints algorithm showed the best path generation results in the autonomous driving microrobot among the three A*-based algorithms.

关键词： A*-WAPP-waypoints autonomous driving microrobot path planning algorithm

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path planning of nanorobot: a review

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MICROSYSTEM TECHNOLOGIES-MICRO-AND NANOSYSTEMS-INFORMATION STORAGE AND PROCESSING SYSTEMS 2022年第11期28卷 2393-2401页

作者： Xu, Ke Su, Rong Shenyang Jianzhu Univ Sch Elect & Control Engn Shenyang 110168 Peoples R China Great Wall Motor Co Ltd Baoding 071000 Peoples R China

Efficient and accurate path planning in a complex biological environment have become a challenge for nanorobot research. This paper first reviews the current path planning algorithms that can be used in the operation of nanorobots in the scientific community. The algorithms are mainly divided into four parts, including Dijkstra algorithm, A* algorithm, Rapidly-exploring Random Tree (RRT) algorithm, and Swarm Intelligence (SI) algorithm. In the application of SI, Genetic algorithm (GA) and Particle Swarm Optimization (PSO) are the most commonly used approaches to solve the path planning of nanorobot swarm. Then, their research status, advantages, and limitations are outlined in each section. The improvement of different algorithms in different environments is discussed while fully demonstrating that they are superior to other methods. Finally, the future research on optimal path planning is expected as the next step in high-precision control of nanorobot. This review aims to provide some ideas for the improvement of nanorobot performance and accelerate another leap of path planning technology in the field of nanomanipulation.

关键词： Nanorobot path planning algorithm Nanomanipulation Drug delivery

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A novel fuzzy inference method for urban incomplete road weight assignment

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地球空间信息科学学报（英文版） 2024年第6期27卷中插15,2008-2022页

作者： Longhao Wang Xiaoping Rui College of Hydrology and Water Resources Hohai UniversityNanjingChina Key Laboratory of Water Cycle and Related Land Surface Processes Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina College of Resources and Environment University of Chinese Academy of SciencesBeijingChina School of Earth Science and Engineering Hohai UniversityNanjingChina

One of the keys in time-dependent routing is determining the weight of each road network link based on traffic *** facilitate the estimation of the road's weight,Global Position System(GPS)data are commonly used in obtaining real-time traffic ***,the information obtained by taxi-GPS does not cover the entire road *** at incom-plete traffic information on urban roads,this paper proposes a novel fuzzy inference *** considers the combined effect of road grade,traffic information,and other spatial *** the third law of geography as the basic premise,that is,the more similar the geogra-phical environment,the more similar the characteristics of the geographical target will *** method uses a Typical Link Pattern(TLP)model to describe the geographical *** TLP represents typical road sections with complete ***,it determines the relationship between roads lacking traffic information and the TLPs according to their related *** obtaining the TLPs,this method ascertains the weight of road links by calculating their similarities with TLPs based on the theory of fuzzy *** at road links at different places,the dividing-conquering strategy and globe algorithm are also introduced to calculate the *** two strategies are used to address the excessively fragmented or lengthy *** experimental results with the case of Newcastle show robustness in that the average Root Mean Square Error(RMSE)is 1.430 mph,and the bias is 0.2％;the overall RMSE is 11.067 mph,and the bias is 0.6％.This article is the first to combine the third law of geography with fuzzy inference,which significantly improves the estimation accuracy of road weights with incomplete *** application and validation show that the method can accurately predict vehicle speed under incomplete information.

关键词： Weight assignment path planning algorithm fuzzy inference road network

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