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Autonomous land vehicle path planning algorithm based on improved heuristic function of A-Star

INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS 2021年第5期18卷

作者： Zhang, Jing Wu, Jun Shen, Xiao Li, Yunsong Xidian Univ State Key Lab Integrated Serv Networks 2South Taibai Rd Xian 710071 Shaanxi Peoples R China

The path planning of autonomous land vehicle has become a research hotspot in recent years. In this article, we present a novel path planning algorithm for an autonomous land vehicle. According to the characteristics of autonomous movement towards the autonomous land vehicle, an improved A-Star path planning algorithm is designed. The disadvantages of using the A-Star algorithm for path planning are that the path planned by the A-Star algorithm contains many unnecessary turning points and is not smooth enough. Autonomous land vehicle needs to adjust its posture at each turning point, which will greatly waste time and also will not be conducive to the motion control of autonomous land vehicle. In view of these shortcomings, this article proposes a new heuristic function combined with the artificial potential field method, which contains both distance information and obstacle information. Our proposed algorithm shows excellent performance in improving the execution efficiency and reducing the number of turning points. The simulation results show that the proposed algorithm, compared with the traditional A-Star algorithm, makes the path smoother and makes the autonomous land vehicle easier to control.

关键词： Autonomous land vehicle path planning algorithm A-Star algorithm artificial potential field heuristic function

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Light weight materials based vehicle secure path planning algorithm for multi constrained QoS routing VANETS

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Materials Today: Proceedings 2021年 47卷 387-390页

作者： R. Dileepkumar B. Nagasri Department of Computer Science and Engineering Saveetha School of Engineering Chennai Tamilnadu India Department of Information Technology Saveetha School of Engineering Chennai Tamilnadu India

As the population is get increases the lightweight materials based vehicles are also get increases. When the people wants to move from the once place to another place they use the transport. As the number of vehicles increases the accident are happening day to day in different place. So the safety in the road is decreases. This paper proposes the VANET’S method which is the vehicle and hoc routing. This method can sends the information about the traffic congestion, road path etc to the mobile network. By using the routing method the safety is increased. In transmitting the data the traffic may happen in the message passing path. Due to this traffic in the routing system a novel path data planning is implemented. The traffic may affect the QOS (Quality of security). So the message transmission is made within a period of time. And this proposed system the supports security measure over the data path. This system is more helpful to the people and it solves a current problem which is taking place. This system is mainly depends on the social problem.

关键词： Lightweight materials Multi-constrained path planning algorithm Reliable routing Vehicular ad hoc networks

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Robot path planning algorithm Based on Particle Swarm Optimization and Feedforward Neural Network in Network Environment 2020

Robot Path Planning Algorithm Based on Particle Swarm Optimi...

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2020 4th International Conference on Artificial Intelligence and Virtual Reality

作者： ShiWei Li Heilongjiang University China

ISBN: (纸本)9781450387996

The main task of mobile robot path planning is: according to the environment model, the mobile robot is based on one or some optimization criteria: such as the minimum work cost, the shortest walking route, the shortest walking time, etc., to find a path in the motion space that does not occur with obstacles. Under the premise of collision, the collision-free path from the starting coordinate point to the target coordinate point allows the robot to reach the destination safely. At present, the path planning methods of mobile robots can be roughly divided into three categories according to their working methods. The first is path planning based on environmental models. It can handle path planning under the condition of fully known obstacle positions and shapes. In the environment, the path planning method based on the environment model will not be applicable. Specific methods such as A * [1], topological graph method [2], etc .; second is local path planning method based on sensor information, typical methods are: artificial potential field method [3], fuzzy logic method [4], etc .; third Behavior-based path planning method [5], which decomposes the navigation problem into independent modules such as collision avoidance and target guidance [6]. Practice shows that it is an effective method to apply neural network to automatic generation of robot trajectory and path planning of mobile robot.

关键词： path planning algorithm WSN Robot PSO

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Robotic platform and path planning algorithm for in situ bioprinting

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Bioprinting 2021年 22卷

作者： Fortunato, Gabriele Maria Rossi, Gabriele Bonatti, Amedeo Franco De Acutis, Aurora Mendoza-Buenrostro, Christian Vozzi, Giovanni De Maria, Carmelo Research Centre “E. Piaggio” University of Pisa Pisa Italy Department of Information Engineering University of Pisa Pisa Italy School of Engineering and Sciences Tecnologico de Monterrey Monterrey Mexico

The aim of this work is to design a robotic bioprinting platform able to fabricate a three-dimensional structure onto irregular surfaces. With respect to the limitations of current in vitro bioprinting approach, widely used in scaffold-based tissue engineering – handling difficulty, risk of contamination, shape not matching with the defect site – this robotic bioprinter can offer an innovative solution allowing in situ bioprinting, a direct dispensing of biological materials onto and into the damaged site. The robotic platform was developed starting from the 5 degrees-of-freedom open source MOVEO robot from BCN3D. The hardware and the software of the original project were re-engineered to control the robot using LinuxCNC, a path planning algorithm was developed in Matlab®, and the end-effector was equipped with a pneumatic extruder. The algorithm automatically projects any generic printing pattern on the surface on which the scaffold will be 3D bioprinted. For each point, the algorithm calculates the joint angles to keep the end effector always perpendicular to the surface. A g-code file is then exported to Linux CNC adding parameters to control the air pressure and the printing speed. The robotic platform was tested to evaluate its performances. Resolution (~200 μm) and repeatability were estimated and preliminary in situ bioprinting tests were performed onto different irregular surfaces, including a physiologically relevant bone model. © 2021 Elsevier B.V.

关键词： In situ bioprinting path planning algorithm Robotic bioprinting platform

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Marine Island UAV Aerial Photography: A path-planning algorithm-Based Study

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JOURNAL OF COASTAL RESEARCH 2020年第Sup1期106卷 642-645页

作者： Wang, Zhiguo Yue, Ping Guangdong Polytech Sci & Technol Dept Guangzhou Coll Guangzhou Guangdong Peoples R China Guangdong Vocat Inst Sports Publ Basic Dept Guangzhou Guangdong Peoples R China

The development of artificial intelligence and information technology provides convenient conditions for the rapid application of unmanned aerial vehicles (UAVs). With more and more fields using UAVs for mission operation, higher requirements are put forward for UAV path planning. In the process of flight, intelligent avoidance of obstacles and autonomous noninterference flight are the hot spots of UAV aircraft planning research. This study first analyzes the key issues that should be considered in UAV path planning, studies the algorithm of UAV path planning based on island aerial photography, and gives the algorithm for optimization of UAV coverage path planning based on island aerial photography.

关键词： Marine island UAV aerial photography path planning algorithm

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A path planning algorithm for industrial processes under velocity constraints with an application to additive manufacturing

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JOURNAL OF MANUFACTURING SYSTEMS 2017年第Part1期43卷 160-167页

作者： Giberti, Hermes Sbaglia, Luca Urgo, Marcello Univ Pavia Dipartimento Ingn Ind & Informaz Via A Ferrata 5 I-27100 Pavia Italy Univ Parma Ind Engn Dept Via Sci 181-A I-43124 Parma Italy Politecn Milan Mech Dept Via Masa 1 I-20156 Milan Italy

In the operation of a broad range of industrial processes, the uses of robots whose trajectories are constrained by the velocity of the parts actuated (tools, end effectors, joints and the like) more often than not play a significant role. Keeping our focus on systems for material deposition such as painting, glueing, aerosol spraying but nowadays also additive manufacturing techniques like FDM processes, it is noticeable that a key parameter is the control of the flow of material in accordance with the trajectory velocity of the parts being actuated. According to the specific requirements and goals of different technology, it is possible to generate different trajectories. In this paper, we propose an original path planning algorithm based on the use of Bezier curves aimed at assuring regulation of the velocity and a uniform distribution of the extruded material referring to an innovative additive manufacturing technology. In particular, the paper presents a path planning technology developed for an application where it is necessary to maintain a constant velocity along the length of the trajectory aimed at improving the technological processes on the basis of an innovative additive technology. The paper further presents a working application with a machine prototype so as to demonstrate the viability and performance of the work under consideration. (C) 2017 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.

关键词： path planning algorithm Bezier curves Additive manufacturing Constant feed rate Constant extrusion rate

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Research on path planning algorithm for Virtual Assembly of Power Battery Packs in New Energy Automobiles

Research on Path Planning Algorithm for Virtual Assembly of ...

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International Conference on Robots & Intelligent System (ICRIS)

作者： Yang Jian-dong Hu Hai-yan Jilin Business & Technol Coll Changchun 130062 Peoples R China Changchun Univ Sci & Technol Coll Mech & Elect Engn Changchun 130062 Peoples R China

ISBN: (纸本)9781509041558

In this paper, based on the existing path planning algorithms for virtual assembly used in other countries, a path planning algorithm for virtual assembly of power battery packs in new energy automobiles based on engineering semantics is put forward in combination with actual characteristics of virtual assembly of power battery packs in new energy automobiles, and such assembly paths for power battery packs can be categorized into linear path, revolving path and mixed path. The path planning algorithm for virtual assembly based on engineering semantic improves planning efficiency for assembly of parts of power battery pack in new energy automobiles.

关键词： Power Battery Pack Virtual Assembly path planning algorithm

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Modified bidirectional rapidly exploring random tree star (Bi-RRT*) algorithm with variable node parameter for optimized path planning in nuclear decommissioning environment

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NUCLEAR ENGINEERING AND DESIGN 2025年 433卷

作者： Adibeli, Justina Onyinyechukwu Liu, Yong-Kuo Chao, Nan Awodi, Ngbede Junior Harbin Engn Univ Fundamental Sci Nucl Safety & Simulat Technol Lab Harbin 150001 Peoples R China Nigeria Atom Energy Commiss Man Power Training & Capac Dev Directorate Abuja Nigeria Nigeria Atom Energy Commiss Nucl Power Plant Dev Directorate Abuja Nigeria

This study introduces an optimized path planning framework employing the modified bidirectional rapidly exploring random tree star (Bi-RRT*) algorithm to enhance navigation efficiency and minimize radiation exposure in nuclear environments. The algorithm integrates a novel variable node parameter approach, dynamically adapting to diverse environmental complexities while prioritizing radiation dose minimization and path planning efficiency. Experimental evaluations across varied scenarios demonstrate that Bi-RRT* achieves substantial improvements over conventional RRT, RRT*, and Bi-RRT algorithms. Simulation results reveal that Bi-RRT* reduces radiation dose by up to 24.14% compared to RRT, 19.27% compared to Bi-RRT, and 3.3% compared to RRT* in cylindrical obstacles scenario. path lengths improve by up to 15.57% over RRT and 11.72% over Bi-RRT in the environment with spherical obstacles, while computational time, although higher, is balanced against significant safety benefits. Configurations with quarter, half, and full nodes highlight a trade-off between dose minimization, computational cost, and path efficiency. The half node configuration consistently provides the best trade-off between computational efficiency and radiation dose optimization, with manageable computational overhead. The full node configuration excels in minimizing path length and radiation dose but incurs the highest computational cost, making it more suitable for applications with abundant computational resources. Conversely, the quarter node configuration prioritizes speed, achieving the fastest computation time but with compromised safety and efficiency, making it ideal for real-time operations where dose minimization is secondary. Analysis across environments with homogeneous and heterogeneous radiation distributions and varying obstacle geometries underscores the algorithm's adaptability and robustness. By achieving superior dose minimization, competitive path lengths, and scalable computat

关键词： path planning algorithm Radiation Decommissioning Nuclear High-risk environment

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Performance Analysis of path planning algorithms for Fruit Harvesting Robot

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JOURNAL OF BIOSYSTEMS ENGINEERING 2023年第2期48卷 178-197页

作者： Zeeshan, Sadaf Aized, Tauseef Univ Cent Punjab Dept Mech Engn Lahore Pakistan Univ Engn & Technol Dept Mech Engn Lahore Pakistan

Purposepath planning is an essential part in designing of an agricultural robot. The path planning algorithms for fruit harvesting robots vary in performance, based on different environments, obstacles, and constraints. This research aims to analyze and evaluate the most commonly used path planning algorithms by fruit harvesting robots in the past 10 years to assess the robot's performance. The primary objective behind the comparative analysis of path planning algorithms is to ascertain which algorithm demonstrates better performance in terms of reaching the target fruit in the shortest time, requiring the least amount of computing resources, and being able to navigate around obstacles effectively. Hence, the study determines which path planning algorithm is the most efficient for the application of fruit harvesting *** this study, four common path planning algorithms were evaluated namely A-star, Probabilistic Road Map, Rapidly exploring Random Tree, and improved Rapidly exploring Random Tree. Three cases were examined for performance. The first case deals with performance based on varying orientations of fruit within the workspace. The second case investigates the performance in the presence of obstacles in the path, and the third case caters to performance due to varying distances of robot and the fruit. Matlab software was used for creating simulation environment for testing. Run time, path length, standard deviation, and total task time were obtained for each case and statistical analysis was *** was found that improved Rapidly exploring Random Tree performed better in terms of path length and gave an optimal path as compared to the other algorithms due to its rewiring feature by an average of 21%. Run time of Rapidly exploring Random Tree was better than the other three *** most commonly used path planning algorithm were analyzed for performance for fruit harvesting robot for three different cases. Despite the variat

关键词： path planning algorithm Fruit harvesting robot Navigation Performance indicators

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A Comparison of Different Hybrid path planning algorithms for a Mobile Platform 4

A Comparison of Different Hybrid Path Planning Algorithms fo...

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4th International Conference on Computer, Control and Robotics (ICCCR)

作者： Sulaiman, Shifa Sudheer, A. P. Magid, Evgeni Kazan Fed Univ Intelligent Robot Dept Kazan Russia Natl Inst Technol Dept Mech Engn Calicut Kerala India HSE Univ Sch Elect Engn Moscow Russia

ISBN: (纸本)9798350373141;9798350373158

Mobile robots with wheeled, legged and hybrid bases are currently used in industrial and service sectors for diverse applications. In this paper, a comparative study of various hybrid path planning algorithms for avoiding static obstacles were carried out for determining a most efficient path planning algorithm for a given task. A modified Probabilistic Road Map (PRM) approach was combined with different versions of A* algorithm to create different hybrid path planning algorithms. The nodes and connections were created using a PRM approach and optimal paths were constructed using different versions of the A* algorithm. This paper compared computational time, memory consumed and path length for determining a suitable hybrid algorithm for a given task. The selected hybrid algorithms were evaluated by simulating an obstacle avoidance task of a mobile robot in a structured environment.

关键词： path planning algorithm Probabilistic Road Map (PRM) A* algorithm mobile robot

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