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8th International Conference on Big Data and Internet of Things

作者： Chen, Jia Zhang, Feizhou Shi, Jing Lv, Hongyan Tsinghua Univ Inst Transportat Engn Beijing Peoples R China China Commun Asset Management Co Ltd Beijing Peoples R China Peking Univ Inst Remote Sensing & GIS Beijing Peoples R China Guangzhou Guojiao Runwan Transportat Informat Co Guangzhou Guangdong Peoples R China

ISBN: (纸本)9798400717529

The purpose of path planning algorithms is to study the shortest path between two points in a topological network. Many scholars at domestic and overseas have conducted in-depth research on this topic, and there are many mature algorithms available. However, the application of path planning in-vehicle navigation systems often focuses on classical static path planning, which cannot cope with large-scale and dynamically changing traffic networks. This paper takes Geographic Information Systems (GIS) as the starting point and uses the ArcGIS traffic network model as the theoretical basis to implement various classical path planning algorithms such as PSP, Dijkstra, DBFS, L-dequeue, L-2queue, improved Dijkstra, A*, and A* bidirectional search. Experimental results show that the algorithm can provide dynamic path planning results based on real-time traffic flow changes, with a running speed nearly an order of magnitude faster than the A* bidirectional search algorithm and nearly five times faster than the ArcGIS path planning algorithm. This is of great significance for optimizing the allocation of road network resources and solving the increasingly serious urban traffic problems.

关键词： Intelligent transportation path planning algorithm Dynamic Bidirectional layering ArcGIS

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A hybrid sampling-based RRT* path planning algorithm for autonomous mobile robot navigation

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EXPERT SYSTEMS WITH APPLICATIONS 2024年 258卷

作者： Ganesan, Sivasankar Ramalingam, Balakrishnan Mohan, Rajesh Elara Amrita Vishwa Vidyapeetham Dept Mech Engn Amrita Sch Engn Coimbatore India Vellore Inst Technol Sch Elect Engn Chennai India Singapore Univ Technol & Design Engn Prod Dev Singapore Singapore

The path-planning algorithms for autonomous mobile robot navigation are crucial, often relying on sampling- based methods. RRT* is a robust, sampling-based path planning algorithm. The sampling process in RRT* plays a pivotal role, where uniform sampling can lead to slow convergence, while non-uniform sampling offers faster convergence but may struggle in complex environments due to its limited exploration. Thus, achieving a balance between exploitation and exploration is essential when selecting the sampling method for the RRT* path-planning algorithm. To address this issue, this research paper introduces Hybrid-RRT*, a path planning method that utilizes hybrid sampling. This unique approach generates samples using both non-uniform and uniform samplers. Hybrid-RRT* is evaluated against three baseline path planning algorithms-RRT*-N, Informed RRT*, and RRT*-across three different 384x384 2D simulation environments. Compared to these baseline methods, Hybrid-RRT* achieves superior results across all five performance metrics: convergence rate, success rate, number of nodes visited, path length, and planning time. According to the numerical results, the proposed algorithm achieves a faster average convergence rate that is 76.14% higher than RRT*, 24% higher than Informed RRT*, and 3.33% higher than RRT*-N. Moreover, it reduces node exploration by an average of 48.53% compared to RRT* and 40.83% compared to Informed RRT*. The simulation results demonstrate that the proposed Hybrid-RRT* algorithm effectively addresses the issue of slow convergence with uniform sampling and the challenge of limited exploration with non-uniform sampling methods.

关键词： Hybrid sampling path planning algorithm RRT Autonomous mobile robot navigation

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

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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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Dual-Arm path-planning algorithm for Wiring Harness Assembly Using Redundantly Actuated Robotic Systems

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IEEE ACCESS 2023年 11卷 98427-98435页

作者： Kim, Jiyoung Kim, Jin-Gyun Park, Jongwoo Han, Byung-Kil Kim, Sanghyun Park, Dong Il Korea Inst Machinery & Mat Dept Robot & Mechatron Yongin 17058 South Korea Kyung Hee Univ Dept Mech Engn Yongin 17104 South Korea

The most challenging task in the wiring harness assembly process is the placement and connection of cables on harness boards. This task remains difficult to automate because it requires dual-arm manipulation to collaboratively grasp the harnesses. In this study, we propose a dual-arm manipulation system and a path-planning framework to automate the wiring harness task. The proposed framework enables the cooperative operation of dual-arm manipulator and plans efficient paths, while considering the kinematic constraints and obstacle avoidance conditions. The framework obtains paths in two steps: 1) the configuration of the robot arms is computed using an inverse kinematics solver;and 2) when the distance between obstacles and robots falls below a certain threshold, a sampling-based algorithm plans paths that satisfy the kinematic constraints and obstacle avoidance conditions. The merits of the framework include a significant reduction in the task time compared to existing methods. This was achieved by efficiently exploring the workspace within the constrained conditions using the proposed algorithm instead of determining the path-planning conditions throughout the entire workspace. The effectiveness of the proposed framework was validated through simulations using redundantly actuated robots with multiple DoF.

关键词： Robots Collision avoidance Task analysis Robot kinematics Kinematics path planning Multi-robot systems Manipulator dynamics cooperative manipulation kinematic constraints dual-arm manipulator path planning algorithm redundantly actuated robotic systems wiring harness assembly

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A path planning algorithm Based on Fusing Lane and Obstacle Map

A Path Planning Algorithm Based on Fusing Lane and Obstacle ...

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IEEE International Conference on Intelligent Transportation Systems

作者： Hao Zhu Mengyin Fu Yi Yang Xinyu Wang Meiling Wang Sch. of Autom. Beijing Inst. of Technol. Beijing China

ISBN: (纸本)9781479960798

This paper proposes a path planning algorithm for autonomous driving in urban environments. The processing of video and Velodyne pointcloud provides information about the positions of lane markers and obstacles in the local map, which are then converted to a lane costmap and obstacle costmap. The referenced GIS follow line is used for generating a series of offset curves, and the best follow line is selected according to a combination of lane, obstacle and background cost. Additional handling of planning path and maximum speed is provided. Our planning algorithm can handle various road types such as U-turn, intersections, and different driving behaviors including passing over or following front vehicles, etc. The proposed navigation framework is implemented on an autonomous vehicle, which exhibits good performance on Future Challenge 2013, Changshu, China.

关键词： geographic information systems image fusion mobile robots path planning road vehicles robot vision video signal processing Velodyne pointcloud autonomous driving autonomous vehicle following front vehicles fusing lane lane costmap obstacle costmap obstacle map path planning algorithm referenced GIS follow line urban environments video processing Cameras Laser radar Mobile robots planning Roads Turning Vehicles

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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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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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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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