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Relevant bibliographies by topics / Avoidance algorithms

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Academic literature on the topic 'Avoidance algorithms'

Author: Grafiati

Published: 25 June 2021

Last updated: 29 July 2025

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Journal articles on the topic "Avoidance algorithms"

1

Yu, Huanchen. "Application of Different Sensors in Obstacle Avoidance of Delivery Robots." Applied and Computational Engineering 80, no. 1 (2024): 81–86. http://dx.doi.org/10.54254/2755-2721/80/2024ch0081.

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People's living conditions are constantly rising as the global economy and society evolve at a rapid pace, and improving production efficiency has become a crucial concern. This paper proposes a combination of multiple obstacle avoidance schemes and algorithms to achieve dynamic obstacle avoidance for delivery robots. By analysing three different obstacle avoidance schemes including visual obstacle avoidance scheme, ultrasonic obstacle avoidance scheme and laser obstacle avoidance scheme, three robot usage scenarios including hotels, restaurants and hospitals, and three vital algorithms includ

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Katona, Kornél, Husam A. Neamah, and Péter Korondi. "Obstacle Avoidance and Path Planning Methods for Autonomous Navigation of Mobile Robot." Sensors 24, no. 11 (2024): 3573. http://dx.doi.org/10.3390/s24113573.

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Path planning creates the shortest path from the source to the destination based on sensory information obtained from the environment. Within path planning, obstacle avoidance is a crucial task in robotics, as the autonomous operation of robots needs to reach their destination without collisions. Obstacle avoidance algorithms play a key role in robotics and autonomous vehicles. These algorithms enable robots to navigate their environment efficiently, minimizing the risk of collisions and safely avoiding obstacles. This article provides an overview of key obstacle avoidance algorithms, includin

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N. Abdulnabi, Ali. "Obstacle Avoidance Techniques for Robot Path Planning." DJES 12, no. 1 (2019): 56–65. http://dx.doi.org/10.24237/djes.2019.12107.

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This paper presents a collision-free path planning approaches based on Bézier curve and A-star algorithm for robot manipulator system. The main problem of this work is to finding a feasible collision path planning from initial point to final point to transport the robot arm from the preliminary to the very last within the presence of obstacles, a sequence of joint angles alongside the path have to be determined. To solve this problem several algorithms have been presented among which it can be mention such as Bug algorithms, A-Star algorithms, potential field algorithms, Bézier curve algorithm

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Gao, Wei, Mengxue Han, Zhao Wang, Lihui Deng, Hongjian Wang, and Jingfei Ren. "Research on Method of Collision Avoidance Planning for UUV Based on Deep Reinforcement Learning." Journal of Marine Science and Engineering 11, no. 12 (2023): 2245. http://dx.doi.org/10.3390/jmse11122245.

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A UUV can perform tasks such as underwater surveillance, reconnaissance, surveillance, and tracking by being equipped with sensors and different task modules. Due to the complex underwater environment, the UUV must have good collision avoidance planning algorithms to avoid various underwater obstacles when performing tasks. The existing path planning algorithms take a long time to plan and have poor adaptability to the environment. Some collision-avoidance planning algorithms do not take into account the kinematic limitations of the UUV, thus placing high demands on the performance and control

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Zhou, Bin, and Jin Fa Qian. "Obstacle Avoidance Control Method of Mobile Robot Motion." Applied Mechanics and Materials 443 (October 2013): 119–22. http://dx.doi.org/10.4028/www.scientific.net/amm.443.119.

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Mobile robot is an intelligent system which can move freely and is scheduled to complete the task in the working environment. Obstacle avoidance of mobile robot is the research hotspot in the control field of the mobile robot. The mobile robot obstacle avoidance methods are classified, including the traditional algorithms and the intelligent algorithms. This paper summarizes the intelligent algorithm in the mobile robot obstacle avoidance technique in the present situation, and the intelligent algorithm which is the most researched in the current. Finally, this paper prospects the development

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Fan, Li. "Research on Autonomous Obstacle Avoidance Algorithm for Complex Environment of Unmanned Aerial Vehicle Based on Multi-source Sensor Fusion." MATEC Web of Conferences 410 (2025): 04008. https://doi.org/10.1051/matecconf/202541004008.

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Autonomous obstacle avoidance for UAVs in complex environments is crucial, single sensors have limitations, and multi-source sensor fusion technology has received attention. Based on the above problems, this paper summarizes the research on autonomous obstacle avoidance algorithms for UAVs in complex environments based on multi- source sensor fusion in recent years. Firstly, the classification and basic principles of multi-source sensor fusion algorithms at the data layer, feature layer and decision layer are sorted out, and the characteristics of commonly used sensors such as LiDAR and vision

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Guo, Binghua, and Nan Guo. "Cash Collection Model of Electric Power Business Office Based on Computer Algorithm." Journal of Physics: Conference Series 2146, no. 1 (2022): 012023. http://dx.doi.org/10.1088/1742-6596/2146/1/012023.

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Abstract With the continuous development of intelligent algorithms, mobile robot (hereinafter referred to as MR) technology is gradually mature, which has been widely used in a variety of industries, such as industry, agriculture, medical treatment, service and so on. With the improvement of intelligent level, people have higher and higher requirements for MRs, which requires MRs to constantly adapt to different environments, especially dynamic environments. In the dynamic environment, obstacle avoidance technology has become the focus of intelligent robot research, which needs to continuously

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Kadry, Seifedine, Gennady Alferov, and Viktor Fedorov. "D-Star Algorithm Modification." International Journal of Online and Biomedical Engineering (iJOE) 16, no. 08 (2020): 108. http://dx.doi.org/10.3991/ijoe.v16i08.14243.

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One of the most effective methods for solving a navigation problem is the method of constructing a navigation system based on the simultaneous localization and mapping algorithm and obstacle avoidance algorithms. One of the most effective obstacles avoidance algorithms is the D-star algorithm [1, 2, 3], which, despite its effectiveness, has some drawbacks. This modification allows to eliminate some problems arising during the implementation of the navigation system.

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Hernandez, Carlos, and Jorge Baier. "Real-Time Adaptive A∗ with Depression Avoidance." Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 7, no. 1 (2011): 146–51. http://dx.doi.org/10.1609/aiide.v7i1.12455.

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RTAA* is probably the best-performing real-time heuristic search algorithm at path-finding tasks in which the environ- ment is not known in advance or in which the environment is known and there is no time for pre-processing. As most real- time search algorithms do, RTAA∗ performs poorly in presence of heuristic depressions, which are bounded areas of the search space in which the heuristic is too low with respect to their border. Recently, it has been shown that LSS-LRTA∗, a well-known real-time search algorithm, can be improved when search is actively guided away of depressions. In this pape

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Zhou, Haiming, Mao Zheng, Xiumin Chu, et al. "Virtual Reality Fusion Testing-Based Autonomous Collision Avoidance of Ships in Open Water: Methods and Practices." Journal of Marine Science and Engineering 12, no. 12 (2024): 2181. http://dx.doi.org/10.3390/jmse12122181.

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With the rapid development of autonomous collision avoidance algorithms on ships, the technical demand for the testing and verification of autonomous collision avoidance algorithms is increasing; however, the current testing of autonomous collision avoidance algorithms is mainly based on the virtual simulation of the computer. To realize the testing and verification of the autonomous collision avoidance algorithm in the real ship scene, a method of virtual reality fusion testing in open water is proposed and real ship testing is carried out. Firstly, an autonomous ship collision avoidance test

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Dissertations / Theses on the topic "Avoidance algorithms"

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Zhang, Wenle. "Scalable deadlock avoidance algorithms for flexible manufacturing systems." Ohio : Ohio University, 2000. http://www.ohiolink.edu/etd/view.cgi?ohiou1179862449.

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Liu, Xintong. "Different techniques for congestion avoidance algorithms in bottleneck networks." Thesis, University of Ottawa (Canada), 2005. http://hdl.handle.net/10393/26961.

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In this thesis, we systematically examine the ECN (Explicit Congestion Notification) mechanism to be applied to some AQM (Active Queue Management) techniques developed in recent years, namely, RED (Random Early Detection), BLUE, ARED (Adaptive RED) and PI-RED (Proportional and Integral RED). We use packet marking as the indication of network congestion, instead of the strategy of dropping packet currently adopted by these AQM algorithms. The performance comparison of ECN-AQM with AQM has been conducted in not only a single bottleneck network but also a multi-bottleneck network environment. The

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Chua, Kee Koon 1965. "Deadlock avoidance: Improved algorithms for centralized and distributed systems." Thesis, The University of Arizona, 1992. http://hdl.handle.net/10150/291335.

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A deadlock avoidance algorithm for a centralized resource allocation system is presented. Unlike the Banker's algorithm, this proposed algorithm makes use of the state of the previous safe sequence to construct a new safe sequence. The performance of this proposed algorithm is compared to that of both the Banker's algorithm and an efficient algorithm proposed by Belik. The simulation results show that our algorithm's execution time is significantly better than the Banker's algorithm and is very competitive with Belik's algorithm. In addition, our Modified Banker's Algorithm produces optimal re

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DE, FILIPPIS LUCA. "Advanced Path Planning and Collision Avoidance Algorithms for UAVs." Doctoral thesis, Politecnico di Torino, 2012. http://hdl.handle.net/11583/2497102.

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The thesis aims to investigate and develop innovative tools to provide autonomous ﬂight capability to a ﬁxed-wing unmanned aircraft. Particularly it contributes to research on path optimization, tra jectory tracking and collision avoidance with two algorithms designed respectively for path planning and navigation. The complete system generates the shortest path from start to target avoiding known obstacles represented on a map, then drives the aircraft to track the optimum path avoiding unpredicted ob jects sensed in ﬂight. The path planning algorithm, named Kinematic A*, is developed on the b

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Rushall, David Aaron 1964. "Efficient heuristics for collision avoidance in three dimensions." Thesis, The University of Arizona, 1989. http://hdl.handle.net/10150/277041.

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This thesis represents a relatively new aspect of computing with regard to robotics. The need for fast, efficient collision avoidance algorithms is growing rapidly. Because conventional methods are complex and require vast amounts of computation, heuristic algorithms are more appealing. The focus of this thesis is the problem of moving a point through three dimensional space while avoiding known polyhedral obstacles. A heuristic algorithm to find shortest (near-optimal) collision-free paths in the presence of polyhedral obstacles, given initial and final positions, is presented. Previous metho

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Conkur, Erdinc Sahin. "Real time path planning and obstacle avoidance algorithms for redundant manipulators." Thesis, University of Bristol, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.389131.

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Pai, Arun S. "Development of deterministic collision-avoidance algorithms for routing automated guided vehicles /." Online version of thesis, 2008. http://hdl.handle.net/1850/7289.

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Ringdahl, Ola. "Techniques and Algorithms for Autonomous Vehicles in Forest Environment." Licentiate thesis, Umeå : Department of Computing Science, Umeå University, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-1314.

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Conrad, Jeremy (Jeremy A. ). "An educational tool to assist students in the evaluation of object avoidance algorithms." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/36302.

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Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2006.<br>Includes bibliographical references (p. 21).<br>Autonomous robots are becoming a part of everyday life. One difficulty in the creation of autonomous robots is having the robots avoid objects. In particular once one has chosen an algorithm difficulty arises in perfecting the parameters involved. Presented here is an implementation of an algorithm and an education support tool add-on to MOOS that allows the end user to quickly vary the parameters to test the performance of the system.<br>by Jeremy Con

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Lee, Hua. "High-Precision Geolocation Algorithms for UAV and UUV Applications in Navigation and Collision Avoidance." International Foundation for Telemetering, 2008. http://hdl.handle.net/10150/606155.

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ITC/USA 2008 Conference Proceedings / The Forty-Fourth Annual International Telemetering Conference and Technical Exhibition / October 27-30, 2008 / Town and Country Resort & Convention Center, San Diego, California<br>UUV homing and docking and UAV collision avoidance are two seemingly separate research topics for different applications. Upon close examination, these two are a pair of dual problems, with interesting correspondences and commonality. In this paper, we present the theoretical analysis, signal processing, and the field experiments of these two algorithms in UAV and UUV applicatio

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Books on the topic "Avoidance algorithms"

1

Goka, Tsuyoshi. Analysis of estimation algorithms for CDTI and CAS applications. Analytical Mechanics Associates, Inc., 1985.

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Goka, Tsuyoshi. Analysis of estimation algorithms for CDTI and CAS applications. Analytical Mechanics Associates, Inc., 1985.

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G, Rojas R., Burnside Walter Dennis 1942-, and United States. National Aeronautics and Space Administration., eds. Modelling and performance analysis of four and eight element TCAS. Ohio State University, Electroscience Laboratory, 1990.

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Narkawicz, Anthony Joseph. State-based implicit coordination and applications. National Aeronautics and Space Administration, Langley Research Center, 2011.

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Center, Ames Research, ed. Cascading a systolic array and a feedforward neural network for navigation and obstacle avoidance using potential fields. National Aeronautics and Space Administration, Ames Research Center, 1991.

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Obstacle Avoidance in Multi-Robot Systems, Experiments in Parallel Genetic Algorithms. World Scientific Publishing Co Pte Ltd, 1998.

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Gill, Mark A. Obstacle Avoidance in Multi-Robot Systems: Experiments in Parallel Genetic Algorithms. World Scientific Publishing Co Pte Ltd, 1998.

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Obstacle Avoidance in Multi-Robot Systems: Experiments in Parallel Genetic Algorithms (World Scientific Series in Robotics and Intelligent Systems , Vol 20). World Scientific Publishing Company, 1998.

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Book chapters on the topic "Avoidance algorithms"

1

Belik, Ferenc. "A distributed deadlock avoidance technique." In Distributed Algorithms. Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/bfb0019801.

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Avni, Hillel, Shlomi Dolev, and Eleftherios Kosmas. "Proactive Contention Avoidance." In Transactional Memory. Foundations, Algorithms, Tools, and Applications. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14720-8_11.

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Nikoletseas, Sotiris, and Olivier Powell. "Obstacle Avoidance Algorithms in Wireless Sensor Networks." In Encyclopedia of Algorithms. Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-2864-4_262.

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Nikoletseas, Sotiris, and Olivier Powell. "Obstacle Avoidance Algorithms in Wireless Sensor Networks." In Encyclopedia of Algorithms. Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-30162-4_262.

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Sharma, Krishneel, Krishan P. Singh, Bhavish P. Gulabdas, Shahil Kumar, Sheikh Izzal Azid, and Rahul Ranjeev Kumar. "Rover with Obstacle Avoidance Using Image Processing." In Algorithms for Intelligent Systems. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-4626-6_37.

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Ofek, Yoram, and Moti Yung. "Efficient mechanism for fairness and deadlock-avoidance in high-speed networks." In Distributed Algorithms. Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/3-540-54099-7_14.

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Molinos, E., J. Pozuelo, A. Llamazares, M. Ocaña, and J. López. "Comparison of Local Obstacle Avoidance Algorithms." In Computer Aided Systems Theory - EUROCAST 2013. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-53862-9_6.

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Fan, Siwen, Wanli Li, and Ruihao Yin. "Research on Path Planning of Concrete Pouring Construction Robot Based on Online Obstacle Avoidance Algorithm." In Lecture Notes in Mechanical Engineering. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-1876-4_80.

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AbstractAiming at the problem of harsh concrete construction environment and low level automation of concrete pouring operation, this paper proposes an autonomous concrete pouring planning method based on real-time obstacle avoidance algorithm. A new 3-DoF articulated concrete pouring robot is designed and kinematically modeled. Rectangular fitting is adopted to simplify irregular obstacles. Then generate obstacle maps and apply intelligent obstacle avoidance algorithms based on the maps, which adopt the reward mechanism in reinforcement learning. The effectiveness of the proposed method in au

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Cook, Robert P., Lifeng Hsu, and Sang H. Son. "Real-Time, Priority-Ordered, Deadlock Avoidance Algorithms." In Foundations of Real-Time Computing: Scheduling and Resource Management. Springer US, 1991. http://dx.doi.org/10.1007/978-1-4615-3956-8_11.

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Salomon, Ralf. "Resampling and its avoidance in genetic algorithms." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0040786.

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Conference papers on the topic "Avoidance algorithms"

1

Yang, Ting, and Xu Li. "Improved DQN-based inspection robot obstacle avoidance path planning." In Third International Conference on Algorithms, Network and Communication Technology (ICANCT 2024), edited by Fabrizio Marozzo. SPIE, 2025. https://doi.org/10.1117/12.3060953.

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S, Babitha, Gowtham N, and H. Sripadarajan. "Accident Avoidance in Driverless Car using Deep Learning Algorithms." In 2025 International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE). IEEE, 2025. https://doi.org/10.1109/iitcee64140.2025.10915470.

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Li, Hui, and Xuliang Duan. "Research Advances in Obstacle Avoidance Path Planning Algorithms for Unmanned Aerial Vehicles." In 2025 2nd International Conference on Algorithms, Software Engineering and Network Security (ASENS). IEEE, 2025. https://doi.org/10.1109/asens64990.2025.11011145.

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Huang, Xiaoqin, and Xu Wang. "Dynamic Obstacle Avoidance for Submarine Cable Laying AUVs Based on Model Prediction." In 2025 8th International Conference on Advanced Algorithms and Control Engineering (ICAACE). IEEE, 2025. https://doi.org/10.1109/icaace65325.2025.11019063.

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Roppel, Thaddeus, Jian Zhang, Yibo Lyu, and Xue Xia. "Corrosion Detection Using Robotic Vehicles in Challenging Environments." In CORROSION 2017. NACE International, 2017. https://doi.org/10.5006/c2017-09741.

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Abstract Navigation algorithms are presented that can be used to guide autonomous vehicles along a right of way to inspect poles or towers for corrosion, or to inspect enclosed spaces such as power substations. These algorithms use the combined methods of sensor feature extraction, PID control, dynamic window obstacle avoidance (DWA), and genetic algorithm (GA) solutions to the traveling-salesman problem (TSP). It is shown through simulation that these algorithms can be used to navigate a wheeled or tracked vehicle in a realistic environment. Results are shown using these algorithms on several

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Sun, Yuhe, and Bing Sun. "MPC Trajectory Tracking and Obstacle Avoidance Control Based on Real-Time Polygon Modeling." In 2025 8th International Conference on Advanced Algorithms and Control Engineering (ICAACE). IEEE, 2025. https://doi.org/10.1109/icaace65325.2025.11019877.

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Ge, Dawei. "Research on obstacle avoidance path planning of robotic manipulator based on deep reinforcement learning." In Fourth International Conference on Advanced Algorithms and Neural Networks (AANN 2024), edited by Qinghua Lu and Weishan Zhang. SPIE, 2024. http://dx.doi.org/10.1117/12.3049584.

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Xiao, Daoyi, Lekang Wang, Yanghui Jing, and Bolun Li. "Machine Learning-Driven Path Planning and Obstacle Avoidance Algorithms for Autonomous Vehicles." In 2025 4th International Symposium on Computer Applications and Information Technology (ISCAIT). IEEE, 2025. https://doi.org/10.1109/iscait64916.2025.11010301.

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Dasgupta, Anubhab, Vedant Zope, and Asrul Harun Ismail. "Implementation of the Bees Algorithm for UAV Mission Plan." In 14th International Seminar on Industrial Engineering and Management. Trans Tech Publications Ltd, 2025. https://doi.org/10.4028/p-nad6qa.

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The increasing use of Unmanned Aerial Vehicles (UAVs) in various applications, such as military operations and civilian tasks, has created a demand for efficient algorithms to plan their mission. This study explores the use of the Bees Algorithm (BA), a nature-inspired optimisation method, to solve two main problems in UAV mission planning: the UAV collision avoidance problem (UCAP) and the Asymmetric TSP (ATSP). Results of comparison between the proposed algorithm and other metaheuristic algorithms indicate that BA can produce competitive solutions. However, the study also found that the BA h

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Zhang, Zheyi, Le Luo, Dongxu Cheng, Hao Yang, and Wenxi Yuan. "Obstacle Avoidance Planning System for Transmission Line Construction Based on Artificial Intelligence Algorithms." In 2024 Second International Conference on Networks, Multimedia and Information Technology (NMITCON). IEEE, 2024. http://dx.doi.org/10.1109/nmitcon62075.2024.10698910.

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Reports on the topic "Avoidance algorithms"

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Stevens, W. TCP Slow Start, Congestion Avoidance, Fast Retransmit, and Fast Recovery Algorithms. RFC Editor, 1997. http://dx.doi.org/10.17487/rfc2001.

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He, Zhitong, Abin Mathew, Abhijeet Ingale, Jue Zhou, Feng Li, and Yaobin Chen. Traffic Management Geocast Study with Connected Vehicles on Indiana Highways. Purdue University, 2024. http://dx.doi.org/10.5703/1288284317753.

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Vehicular communication allows vehicles to interact with road users, roadside infrastructure, and cloud-connected devices. It holds a crucial position in modern transportation systems, impacting both fundamental and advanced aspects and enhancing traffic safety and efficiency. C-V2X is a wireless communication technology that uses cellular networks to enable communication between vehicles and infrastructure. C-V2X can be used for applications such as collision avoidance, traffic management, and remote vehicle diagnostics. This project conducted a feasibility study on the current position of C-

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Von Wahlde, Raymond, Nathan Wiedenman, Wesley A. Brown, and Cezarina Viqueira. An Open-Path Obstacle Avoidance Algorithm Using Scanning Laser Range Data. Defense Technical Information Center, 2009. http://dx.doi.org/10.21236/ada494907.

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Rear End Crash Avoidance System (RECAS) Algorithms and Alerting Strategies. University of Iowa Public Policy Center, 2006. http://dx.doi.org/10.17077/q89n-flvk.

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