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6th Iberian Robotics Conference (Robot)

作者： Ferreira, Edilson Grilo, Vinicius Braun, Joao Santos, Murillo Pereira, Ana I. Costa, Paulo Lima, Jose Inst Politecn Braganca Res Ctr Digitalizat & Intelligent Robot CeDRI P-5300253 Braganca Portugal Ctr Fed Educ Tecnol Minas Gerais CEFET MG Belo Horizonte MG Brazil Inst Politecn Braganca Lab Associado Sustentabilidade & Tecnol Regioes M Campus Santa Apolonia P-5300253 Braganca Portugal INESC TEC Robot & Intelligent Syst Res Grp P-4200465 Porto Portugal Univ Porto FEUP Fac Engn Rua Dr Roberto Frias P-4200465 Porto Portugal

ISBN: (纸本)9783031586750;9783031586767

This article presents the development of a low-cost 3D mapping technology for trajectory planning using a 2D LiDAR and a stepper motor. The research covers the design and implementation of a circuit board to connect and control all components, including the LiDAR and motor. In addition, a 3D printed support structure was developed to connect the LiDAR to the motor shaft. System data acquisition and processing are addressed, as well as the generation of the point cloud and the application of the A* algorithm for trajectory planning. Experimental results demonstrate the effectiveness and feasibility of the proposed technology for low-cost 3D mapping and trajectory planning applications.

关键词： path planning algorithm A LiDAR

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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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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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Homotopy path planning for Terrestrial Robots Using Spherical algorithm

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2018年第2期15卷 567-585页

作者： Diaz-Arango, Gerardo Vazquez-Leal, Hector Hernandez-Martinez, Luis Sanz Pascual, Maria Teresa Sandoval-Hernandez, Mario Natl Inst Astrophys Opt & Elect Elect Dept Puebla 72840 Mexico Univ Veracruzana Elect Instrumentat & Atmospher Sci Sch Xalapa 91000 Veracruz Mexico Univ Xalapa Ciencia Cultura & Tecnol Xalapa 91190 Veracruz Mexico Ctr Bachillerato Tecnol Ind & Serv Veracruz 91777 Veracruz Mexico

Autonomous and semiautonomous mobile robots play an important role in making tasks in environments considered hostile or dangerous for a human being. In order to execute many of the required tasks, robots need, in its architecture, a module of navigation with an appropriate path planning algorithm. This paper presents the development and implementation of a methodology for path planning of a mobile robot using a spherical algorithm and homotopy continuation methods (HCMs). The first section is a brief introduction about HCMs. Subsequently, the homotopy path planning method and spherical path tracking algorithm are explained, as well as the upgraded version and its main features. Then, the main contributions of this paper are presented and the effectiveness of the proposed method is proved. Besides, numerical examples, implementation results in multiple platforms including a 32b microcontroller and robot operating system, are displayed. Finally, some favorable results from a comparative between the proposed methodology against sampling-based planners using the open motion planning library are presented.

关键词： Homotopy continuation methods (HCMs) mobile robotics open motion planning library path planning algorithm robot operating system (ROS) spherical path tracking algorithm

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A New path planning and Obstacle Avoidance algorithm in Dynamic Environment 22

A New Path Planning and Obstacle Avoidance Algorithm in Dyna...

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22nd Iranian Conference on Electrical Engineering (ICEE)

作者： Mohammadi, Afshin Rahimi, Meysam Suratgar, Amir Abolfazl Amirkabir Univ Technol Dept Elect Engn Tehran Iran

ISBN: (纸本)9781479944095

By developments of robotics and increments in utilizing this knowledge in different scientific and industrial branches, the issue of path planning, either in intelligent and online state, or by pre-determined algorithms has been arised as one of the discussion fields in control and specially robotics. In the path planning literature, several algorithms have been used repetitively, among which can be mentioned potential field algorithms and intelligent algorithms such as genetic and A-Star, in which the main challenge is to find an obstacle free path, not considering capabilities like computation time, considering obstacles in path finding procedure. In this paper, we developed a new path planning algorithm, not only find an obstacle-free path but also has an optimal computation time in term of obstacle importance and consider the issues like adjustable obstacle avoidance and smoothness of the final path. The intention of this paper is introducing a path planning which is able to be applied in a typical needle penetration surgery. The proposed algorithm, by suitable environment segmentation, as hexagonal segmentation, concludes to a path, that is very smoother than pathes which are resulted in other traditional algorithms.

关键词： collision avoidance medical robotics mobile robots surgery dynamic environment needle penetration surgery obstacle avoidance algorithm path planning algorithm Collision avoidance Heuristic algorithms Indexes Needles path planning Robots Surgery

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Three Dimensional D* algorithm for Incremental path planning in Uncooperative Environment 3

Three Dimensional D* Algorithm for Incremental Path Planning...

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3rd International Conference on Signal Processing and Integrated Networks (SPIN)

作者： Majumder, Shibarchi Prasad, Mani Shankar Indian Inst Space Sci & Technol Thiruvananthapuram Kerala India

ISBN: (纸本)9781467391979

path planning algorithms play a significant role in autonomous navigation problems. There are several algorithms to compute the optimal path through a cooperative environment. However, for uncooperative environment, finding the global minima is not certain. There are effective algorithms like dynamic A* (D*), for finding an efficient path in uncooperative two dimensional spaces using the concept of local minima. For three dimensional spaces the problem becomes more complex as the traverse cost is dynamic for Z axis. We propose an algorithm for incremental path finding throughout the flight regime, as a concept modification of D*, to work on 3D environment.

关键词： Incremental path planning Uncooperative Environment path planning algorithm Obstacle Handling Edge Point UAV path-planning

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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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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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Mobile robot for leaf disease detection and precise spraying: Convolutional neural networks integration and path planning

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SCIENTIFIC AFRICAN 2025年 28卷

作者： Bouhaja, Youssef Bamoumen, Hatim Derdak, Israe Sheikh, Safiyah El Azhari, Moulay El Hassan El Hafdaoui, Hamza Al Akhawayn Univ Sch Sci & Engn Ifrane 53000 Morocco Sidi Mohamed Ben Abdellah Univ Natl Sch Appl Sci Fes 30000 Morocco

Plant diseases are a major cause of crop yield and quality losses, particularly in tomatoes, where bacterial, fungal, and viral diseases significantly impact production. Traditional disease detection methods are slow and prone to human error, limiting their use in large-scale agriculture. This study presents a mobile robot equipped with a custom convolutional neural network (CNN)-based system for early-stage disease detection and pesticide spraying;the robot was trained and tested on 13,191 tomato leaf images, using an 80:20 train-test split. The robot features a Raspberry Pi (ARM Cortex-A72, 1.5 GHz, 4 GB RAM) for processing, an RGB camera (12 MP, 30 fps), and a LiDAR module (360 degrees range, 12 m, 0.1 degrees resolution) for navigation. The pesticide spraying mechanism is driven by an Arduino-controlled stepper motor (1.8 degrees step angle) with precise 180 degrees movement for targeted application. The system was evaluated based on performance and efficiency evaluation, cost-effectiveness, environmental impact assessment, and sensitivity analysis. In navigation tests, the robot maintained minimal deviation of 1 cm in open fields, with fast obstacle detection and path adjustment in dynamic environments, including obstacles detected within 150 milliseconds. The robot achieved a precision rate of 95 % after just 50 epochs of training with a real-time latency of 0.015 s per image classification, which significantly outperforms the highest precision rate of 91 % achieved at 70 epochs from literature, where the realtime latency exceeded 0.028 s. Validation accuracy remained between 85 % and 90 %, indicating strong generalization. Classification metrics showed exceptional performance, with accuracy, precision, recall, and F1-scores all exceeding 91 % across 10 tomato leaf classes. The confusion matrix showed minimal misclassifications, and the receiver operating characteristic curve confirmed the model's strong ability to differentiate between healthy and diseased le

关键词： Convolutional neural network Mobile robot Leaf disease detection Pesticide spraying path planning algorithm

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