Relevant bibliographies by topics / Autonomous algorithms

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Autonomous algorithms'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Autonomous algorithms"

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Tang, Yuexia, Muhammad Aizzat Zakaria, and Maryam Younas. "Path Planning Trends for Autonomous Mobile Robot Navigation: A Review." Sensors 25, no. 4 (2025): 1206. https://doi.org/10.3390/s25041206.

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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 te
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Xu, Xincheng. "Research on visual SLAM for dynamic scenes." Applied and Computational Engineering 12, no. 1 (2023): 34–38. http://dx.doi.org/10.54254/2755-2721/12/20230291.

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Simultaneous Localization and Mapping (SLAM) technology has many applications, such as intelligent robots, autonomous driving, and smart cities. It is a key technology for achieving autonomous robot navigation and environmental awareness. Robots need to perceive the surrounding environment in real-time and construct maps while conducting autonomous localization and path planning, which involves algorithms of SLAM technology. This article aims to introduce the research on visual SLAM algorithms in dynamic scenes. This article will first introduce the traditional SLAM algorithm, its research sta
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Caselli, Nicolás, Ricardo Soto, Broderick Crawford, Sergio Valdivia, Elizabeth Chicata, and Rodrigo Olivares. "Dynamic Population on Bio-Inspired Algorithms Using Machine Learning for Global Optimization." Biomimetics 9, no. 1 (2023): 7. http://dx.doi.org/10.3390/biomimetics9010007.

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In the optimization field, the ability to efficiently tackle complex and high-dimensional problems remains a persistent challenge. Metaheuristic algorithms, with a particular emphasis on their autonomous variants, are emerging as promising tools to overcome this challenge. The term “autonomous” refers to these variants’ ability to dynamically adjust certain parameters based on their own outcomes, without external intervention. The objective is to leverage the advantages and characteristics of an unsupervised machine learning clustering technique to configure the population parameter with auton
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Shi, Shangzhe. "Research Status of Autonomous Vehicle Path Planning." SHS Web of Conferences 144 (2022): 02019. http://dx.doi.org/10.1051/shsconf/202214402019.

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In recent years, many companies have been developing path planning algorithms and hardware for autonomous vehicles. This paper mainly introduces the latest research and applications of path planning algorithms and related hardware for autonomous vehicles. The introduced algorithms include improvements to Traditional Algorithms, Intelligent Optimization Algorithms, Reinforcement Learning Algorithms and Hybrid Algorithms, such as improving algorithm running speed, path planning ability, and environment learning speed. In terms of hardware research and application, due to the rise of sensor techn
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Bykova, V. S., A. I. Mashoshin, and I. V. Pashkevich. "Safe Navigation Algorithm for Autonomous Underwater Vehicles." Giroskopiya i Navigatsiya 29, no. 1 (2021): 97–110. http://dx.doi.org/10.17285/0869-7035.0058.

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Two safe navigation algorithms for autonomous underwater vehicles are described: algorithm for avoidance of point obstacles including all the moving underwater and surface objects, and limited size bottom objects, and algorithm for bypassing extended obstacles such as bottom elevations, rough lower ice edge, garbage patches. These algorithms are developed for a control system of a heavyweight autonomous underwater vehicle.
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Sathyamangalam Imran, Mohammed Irshadh Ismaaeel, Satyesh Shanker Awasthi, Michael Khayyat, Stefano Arrigoni, and Francesco Braghin. "Virtual Validation and Uncertainty Quantification of an Adaptive Model Predictive Controller-Based Motion Planner for Autonomous Driving Systems." Future Transportation 4, no. 4 (2024): 1537–58. https://doi.org/10.3390/futuretransp4040074.

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In the context of increasing research on algorithms for different modules of the autonomous driving stack, the development and evaluation of these algorithms for deployment onboard vehicles is the next critical step. In the development and verification phases, simulations play a pivotal role in achieving this aim. The uncertainty quantification of Autonomous Vehicle (AV) systems could be used to enhance safety assurance and define the error-handling capabilities of autonomous driving systems (ADSs). In this paper, a virtual validation methodology for the control module of an autonomous driving
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He, Weikun. "Analysis of the Applications of Algorithm and Automatic Pathfinding." Applied and Computational Engineering 109, no. 1 (2024): 97–102. http://dx.doi.org/10.54254/2755-2721/109/20241456.

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Abstract. The current development of autonomous driving technology is very hot, which involves two fundamental aspects: one is the operating system as the foundation, and the other is the algorithm application. The theme of this review is to study the related algorithmic technologies and combine them with one of the key functions of autonomous driving: autonomous routing. The review discusses the application direction and environment of this function, and involves the use of algorithms in the backend. Autonomous routing is a key concept in multiple technical fields and plays an important role
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ANDRECUT, M., and M. K. ALI. "DEEP-SARSA: A REINFORCEMENT LEARNING ALGORITHM FOR AUTONOMOUS NAVIGATION." International Journal of Modern Physics C 12, no. 10 (2001): 1513–23. http://dx.doi.org/10.1142/s0129183101002851.

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In this paper we discuss the application of reinforcement learning algorithms to the problem of autonomous robot navigation. We show that the autonomous navigation using the standard delayed reinforcement learning algorithms is an ill posed problem and we present a more efficient algorithm for which the convergence speed is greatly improved. The proposed algorithm (Deep-Sarsa) is based on a combination between the Depth-First Search (a graph searching algorithm) and Sarsa (a delayed reinforcement learning algorithm).
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Arunprasad, Veeranan, Brijendra Gupta, Karthikeyan T, and Muruganantham Ponnusamy. "HYBRID NEURO-FUZZY-GENETIC ALGORITHMS FOR OPTIMAL CONTROL OF AUTONOMOUS SYSTEMS." ICTACT Journal on Soft Computing 13, no. 4 (2023): 3015–20. http://dx.doi.org/10.21917/ijsc.2023.0424.

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In recent years, there has been an increasing demand for efficient and robust control algorithms to optimize the performance of autonomous systems. Traditional control techniques often struggle to handle the complexity and uncertainty associated with such systems. To address these challenges, hybrid neuro-fuzzy-genetic algorithms have emerged as a promising approach. This paper presents a comprehensive review of the application of hybrid neuro-fuzzy-genetic algorithms for optimal control of autonomous systems. The proposed algorithms combine the strengths of neural networks, fuzzy logic, and g
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Goldman, R. E., A. Bajo, and N. Simaan. "Algorithms for autonomous exploration and estimation in compliant environments." Robotica 31, no. 1 (2012): 71–87. http://dx.doi.org/10.1017/s0263574712000100.

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SUMMARYThis paper investigates algorithms for enabling surgical slave robots to autonomously explore shape and stiffness of surgical fields. The paper addresses methods for estimating shape and impedance parameters of tissue and methods for autonomously exploring perceived impedance during tool interaction inside a tissue cleft. A hybrid force-motion controller and a cycloidal motion path are proposed to address shape exploration. An adaptive exploration algorithm for segmentation of surface features and a predictor-corrector algorithm for exploration of deep features are introduced based on d
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Dissertations / Theses on the topic "Autonomous algorithms"

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Skoglund, Martin. "Evaluating SLAM algorithms for Autonomous Helicopters." Thesis, Linköping University, Department of Electrical Engineering, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-12282.

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<p>Navigation with unmanned aerial vehicles (UAVs) requires good knowledge of the current position and other states. A UAV navigation system often uses GPS and inertial sensors in a state estimation solution. If the GPS signal is lost or corrupted state estimation must still be possible and this is where simultaneous localization and mapping (SLAM) provides a solution. SLAM considers the problem of incrementally building a consistent map of a previously unknown environment and simultaneously localize itself within this map, thus a solution does not require position from the GPS receiver.</p><p
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Hofer, Ludovic. "Decision-making algorithms for autonomous robots." Thesis, Bordeaux, 2017. http://www.theses.fr/2017BORD0770/document.

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Afin d'être autonomes, les robots doivent êtres capables de prendre des décisions en fonction des informations qu'ils perçoivent de leur environnement. Cette thèse modélise les problèmes de prise de décision robotique comme des processus de décision markoviens avec un espace d'état et un espace d'action tous deux continus. Ce choix de modélisation permet de représenter les incertitudes sur le résultat des actions appliquées par le robot. Les nouveaux algorithmes d'apprentissage présentés dans cette thèse se focalisent sur l'obtention de stratégies applicables dans un domaine embarqué. Ils sont
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Sidi, Bah Aladé Habib. "Distributed algorithms in autonomous and heterogeneous networks." Thesis, Avignon, 2012. http://www.theses.fr/2012AVIG0184/document.

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La diversité croissante des différents agents constituant les réseaux de communication actuels ainsi que la capacité accrue des technologies concurrentes dans l’environnement réseau a conduit à la prise en compte d’une nouvelle approche distribuée de la gestion du réseau. Dans cet environnement réseau évolué, le besoin en accroissement de la bande passante et en ressources rares, s’oppose à la réduction de la consommation énergétique globale.Dans notre travail nous nous intéressons à l’application de mécanismes distribués et de méthodes d’apprentissages visant à introduire d’avantage d’autonom
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Bsaybes, Sahar. "Models and algorithms for fleet management of autonomous vehicles." Thesis, Université Clermont Auvergne‎ (2017-2020), 2017. http://www.theses.fr/2017CLFAC114/document.

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Résumé indisponible<br>The VIPAFLEET project aims at developing a framework to manage a fleet of IndividualPublic Autonomous Vehicles (VIPA). We consider a fleet of cars distributed at specifiedstations in an industrial area to supply internal transportation, where the cars can beused in different modes of circulation (tram mode, elevator mode, taxi mode). The goalis to develop and implement suitable algorithms for each mode in order to satisfy all therequests either under an economic point aspect or under a quality of service aspect, thisby varying the studied objective functions.We model the
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Chaudhari, Pratik (Pratik Anil). "Algorithms for autonomous urban navigation with formal specifications." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/90726.

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Thesis: E.A.A., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2014.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 58-62).<br>This thesis addresses problems in planning and control of autonomous agents. The central theme of this work is that integration of "low-level control synthesis" and "high-level decision making" is essential to devise robust algorithms with provable guarantees on performance. We pursue two main directions here. The first part considers planning and control algorithms that satisfy temporal specif
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Everett, Michael F. "Algorithms for robust autonomous navigation in human environments." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/129052.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2020<br>Cataloged from student-submitted PDF of thesis.<br>Includes bibliographical references (pages 143-163).<br>Today's robots are designed for humans, but are rarely deployed among humans. This thesis addresses problems of perception, planning, and safety that arise when deploying a mobile robot in human environments. A first key challenge is that of quickly navigating to a human-specified goal - one with known semantic type, but unknown coordinate - in a previously unseen world. This thesis formul
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Běhal, Lukáš. "An Autonomous Driver of a TORCS Racing Car." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2012. http://www.nusl.cz/ntk/nusl-236619.

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Tato práce popisuje simulátor TORCS a optimalizační algoritmy, jenž jsou využívány při tvorbě autonomních řidičů pro tento simulátor. Hlavním cílem je navržení nového autonomního řidiče, který se bude schopen s použitím přírodou inspirovaných optimalizačních technik vyrovnat již dříve navrženým řešením. Chování implementovaného řešení lze rozdělit do dvou hlavních částí, které jsou využívány v různých rozdílných etapách závodu. Zahřívací kolo je využito pro vytvoření modelu trati, ze kterého je posléze získána optimální trajektorie pomocí genetického algoritmu. Této trajektorie je potom využív
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Oetiker, Moritz Benjamin. "Real-time control algorithms for semi-autonomous parking assistants /." Zürich : ETH Institut für Mess- und Regeltechnik, 2009. http://e-collection.ethbib.ethz.ch/show?type=diss&nr=18229.

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Rognsvåg, Jan Vidar. "Autonomous Algorithms for Dynamic Spectrum Management in DSL Systems." Thesis, Norwegian University of Science and Technology, Department of Electronics and Telecommunications, 2008. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-8934.

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<p>Krysstale mellom tvinnede parkabler er blitt den dominerende kilden for interferens i dagens DSL (Digital Subscriber Lines) systemer. I eksisterende standarder er det satt maksimalverdier for utsendt effekttetthet basert på estimat av verste tilfelle interferens for alle par-til-par kombinasjoner av krysstale med følgelig begrensninger i overføringskapasitet. Videre blir effekt statisk tildelt over hele den tilgjengelige båndbredden uten hensyn til frekvensavhengig attenuasjon og interferens i metoder basert på statisk frekvensbruk (SSM - Static Spectrum Management). Dette arbeidet tar fo
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Jarne, Ornia Daniel. "Ant Colony Algorithms andits applications to Autonomous Agents Systems." Thesis, KTH, Optimeringslära och systemteori, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-217391.

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With the latest advancements in autonomous agents systems and technology, there is a growing interest in developing control algorithms and methods to coordinate large numbers of robotic entities. Following this line of work, the use of biologically inspired algorithms based on swarm emerging behaviour presents some really interesting properties for controlling multiple agents. They rely on very simple instructions and communications to develop a coordinated structure in the system. Particularly, this master thesis focuses on the study of Ant Colony algorithms based on stigmergy interaction to
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Books on the topic "Autonomous algorithms"

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Hamadi, Youssef, Eric Monfroy, and Frédéric Saubion. Autonomous search. Springer, 2011.

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service), SpringerLink (Online, ed. Autonomous Intelligent Vehicles: Theory, Algorithms, and Implementation. Springer-Verlag London Limited, 2011.

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Diamadopoulos. Lane support algorithms for autonomous vehicle navigation. UMIST, 1996.

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Ren, Jianfeng, and Dong Xia. Autonomous driving algorithms and Its IC Design. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-2897-2.

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Chatterjee, Amitava. Vision Based Autonomous Robot Navigation: Algorithms and Implementations. Springer Berlin Heidelberg, 2013.

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Almássy, Nikolaus. Genetic evolution of autonomous agents. Shaker, 1995.

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Ren, Jianfeng. Autonomous driving algorithms and its IC design - Part One. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-8041-3.

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Ren, Jianfeng. Autonomous driving algorithms and its IC design - Part Two. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-8040-6.

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Fanelli, Francesco. Development and Testing of Navigation Algorithms for Autonomous Underwater Vehicles. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-15596-4.

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Michela, Azzariti, Stark Lawrence W, and United States. National Aeronautics and Space Administration., eds. Autonomous image processing algorithms locate region-of-interests: The Mars Rover application. Electronics Research Laboratory, College of Engineering, University of California, 1998.

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Book chapters on the topic "Autonomous algorithms"

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Hamadi, Youssef. "Autonomous Search." In Combinatorial Search: From Algorithms to Systems. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41482-4_7.

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Maturana, Jorge, Álvaro Fialho, Frédéric Saubion, Marc Schoenauer, Frédéric Lardeux, and Michèle Sebag. "Adaptive Operator Selection and Management in Evolutionary Algorithms." In Autonomous Search. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21434-9_7.

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Baumann, Cyrill, Jonas Perolini, Emna Tourki, and Alcherio Martinoli. "Hybrid Flock - Formation Control Algorithms." In Distributed Autonomous Robotic Systems. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-51497-5_37.

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Ren, Jianfeng, and Dong Xia. "Autonomous Driving ASICs." In Autonomous driving algorithms and Its IC Design. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-2897-2_7.

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Ren, Jianfeng, and Dong Xia. "Autonomous Driving Simulator." In Autonomous driving algorithms and Its IC Design. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-2897-2_6.

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Leal, Ana Alves. "Algorithms, Creditworthiness, and Lending Decisions." In Legal Aspects of Autonomous Systems. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-47946-5_17.

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Sklyarov, Valery, Iouliia Skliarova, and Bruno Pimentel. "FPGA-Based Implementation of Graph Colouring Algorithms." In Autonomous Robots and Agents. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73424-6_26.

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Ren, Jianfeng, and Dong Xia. "Autonomous Driving Operating Systems." In Autonomous driving algorithms and Its IC Design. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-2897-2_11.

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Ren, Jianfeng, and Dong Xia. "Autonomous Driving Software Architecture." In Autonomous driving algorithms and Its IC Design. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-2897-2_12.

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Ren, Jianfeng, and Dong Xia. "Autonomous Driving SoC Design." In Autonomous driving algorithms and Its IC Design. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-2897-2_10.

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Conference papers on the topic "Autonomous algorithms"

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C R, Komala, J. Raja, Sarange Shreepad Marotrao, Nalla Neelima, R. Sujatha, and K. Chidambarathanu. "AI algorithms for Autonomous Robotics Navigation." In 2024 Second International Conference Computational and Characterization Techniques in Engineering & Sciences (IC3TES). IEEE, 2024. https://doi.org/10.1109/ic3tes62412.2024.10877509.

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H T, Madan, Mahesh L, and Mohammed Sajjad. "ROS Powered Autonomous Mobile Robot for Indoor Applications." In 2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS). IEEE, 2024. http://dx.doi.org/10.1109/iacis61494.2024.10721860.

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Li, Mengqi, Qin Hu, Ying Shi, and Chaojun Lin. "An Improved Grounding DINO Algorithm for Autonomous Driving." In 2025 8th International Conference on Advanced Algorithms and Control Engineering (ICAACE). IEEE, 2025. https://doi.org/10.1109/icaace65325.2025.11019922.

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Sai, T. Sitanshu, Rohit Singavarapu, Adithya Penala, Boya Rakesh, and Anjali T. "Cyberbullying Detection Using QDA and LDA Algorithms." In 2025 International Conference on Machine Learning and Autonomous Systems (ICMLAS). IEEE, 2025. https://doi.org/10.1109/icmlas64557.2025.10968812.

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Roberts, Andrew, Mohammad Reza Heidari Iman, Mauro Bellone, et al. "ADAssure: Debugging Methodology for Autonomous Driving Control Algorithms." In 2024 Design, Automation & Test in Europe Conference & Exhibition (DATE). IEEE, 2024. http://dx.doi.org/10.23919/date58400.2024.10546519.

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Jawade, Nikhil, Elvira Castello, James Whicker, et al. "Snapshot HSI video implications for ground reconnaissance and autonomous navigation." In Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXXI, edited by David W. Messinger and Miguel Velez-Reyes. SPIE, 2025. https://doi.org/10.1117/12.3053660.

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Yan, Qiyan, Zhoulin Chang, and Xia Liu. "Research on the application of deep learning in autonomous vehicle." 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/10.1117/12.3049797.

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Venkatesam, Anne Sreyas, Karnati Shainy Reddy, Shanmugasundaram Hariharan, Bibhuti Bhsan Dash, Subrata Chowdhury, and Sudhansu Shekhar Patra. "Optimizing Blockchain Mining Decisions Using Deep Reinforcement Learning Algorithms." In 2025 International Conference on Machine Learning and Autonomous Systems (ICMLAS). IEEE, 2025. https://doi.org/10.1109/icmlas64557.2025.10967840.

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SOKRATOVA, OLGA. "AUTOMATA IN AUTONOMOUS VARIETIES." In Semigroups, Algorithms, Automata and Languages. WORLD SCIENTIFIC, 2002. http://dx.doi.org/10.1142/9789812776884_0018.

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Danks, David, and Alex John London. "Algorithmic Bias in Autonomous Systems." In Twenty-Sixth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/654.

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Algorithms play a key role in the functioning of autonomous systems, and so concerns have periodically been raised about the possibility of algorithmic bias. However, debates in this area have been hampered by different meanings and uses of the term, "bias." It is sometimes used as a purely descriptive term, sometimes as a pejorative term, and such variations can promote confusion and hamper discussions about when and how to respond to algorithmic bias. In this paper, we first provide a taxonomy of different types and sources of algorithmic bias, with a focus on their different impacts on the
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Reports on the topic "Autonomous algorithms"

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Seitzer, Jennifer. Battle Management Algorithms for Autonomous Unmanned Systems (BMAAUS). Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada421313.

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Iagnemma, Karl. Threat-Based Semi-Autonomous Operator Assistance Algorithms for Ground Vehicles. Defense Technical Information Center, 2013. http://dx.doi.org/10.21236/ada616184.

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Kwiat, Paul, Eric Chitambar, Andrew Conrad, and Samantha Isaac. Autonomous Vehicle-Based Quantum Communication Network. Illinois Center for Transportation, 2022. http://dx.doi.org/10.36501/0197-9191/22-020.

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Quantum communication was demonstrated using autonomous vehicle-to-vehicle (V2V), as well as autonomous vehicle-to-infrastructure (V2I). Supporting critical subsystems including compact size, weight, and power (SWaP) quantum sources; optical systems; and pointing, acquisition, and tracking (PAT) subsystems were designed, developed, and tested. Novel quantum algorithms were created and analyzed, including quantum position verification (QPV) for mobile autonomous vehicles. The results of this research effort can be leveraged in support of future cross-platform, mobile quantum communication netwo
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Hovakimyan, Naira. Development of Adaptive Algorithms for Visual Control of Autonomous Multi-Vehicle Systems. Defense Technical Information Center, 2009. http://dx.doi.org/10.21236/ada512547.

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Glaspell, Garry, Amir Naser, Kenneth Niles, Maribel Delatorre, Dylan Charter, and Ahmet Soylemezoglu. Robot Operating System innovations in autonomous navigation. Engineer Research and Development Center (U.S.), 2025. https://doi.org/10.21079/11681/49746.

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This report presents the results of simulations conducted in preparation for the 2024 Maneuver Support and Protection Integration Experiments (MSPIX) demonstration. The study aimed to develop and test a system for autonomous navigation in complex environments using advanced algorithms to enable the robot to avoid obstacles and navigate safely and efficiently. The report describes the methodology used to develop and test the autonomous navigation system, including the use of simulation, to evaluate its performance. The results of the simulation tests are presented to highlight the effectiveness
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Pasupuleti, Murali Krishna. Optimal Control and Reinforcement Learning: Theory, Algorithms, and Robotics Applications. National Education Services, 2025. https://doi.org/10.62311/nesx/rriv225.

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Abstract: Optimal control and reinforcement learning (RL) are foundational techniques for intelligent decision-making in robotics, automation, and AI-driven control systems. This research explores the theoretical principles, computational algorithms, and real-world applications of optimal control and reinforcement learning, emphasizing their convergence for scalable and adaptive robotic automation. Key topics include dynamic programming, Hamilton-Jacobi-Bellman (HJB) equations, policy optimization, model-based RL, actor-critic methods, and deep RL architectures. The study also examines traject
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Grenander, Ulf. Performance Modelling of Autonomous Electro-Optical Sensors. Experimental Algorithms and Software for ATR. Defense Technical Information Center, 1987. http://dx.doi.org/10.21236/ada230948.

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Wang, Shenlong, and David Forsyth. Safely Test Autonomous Vehicles with Augmented Reality. Illinois Center for Transportation, 2022. http://dx.doi.org/10.36501/0197-9191/22-015.

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This work exploits augmented reality to safely train and validate autonomous vehicles’ performance in the real world under safety-critical scenarios. Toward this goal, we first develop algorithms that create virtual traffic participants with risky behaviors and seamlessly insert the virtual events into real images perceived from the physical world. The resulting composed images are photorealistic and physically grounded. The manipulated images are fed into the autonomous vehicle during testing, allowing the self-driving vehicle to react to such virtual events within either a photorealistic sim
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Gibbons, S., F. Ringdal, and D. Harris. NORSAR Final Scientific Report Adaptive Waveform Correlation Detectors for Arrays: Algorithms for Autonomous Calibration. Office of Scientific and Technical Information (OSTI), 2009. http://dx.doi.org/10.2172/952085.

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Lewis, Dustin, Naz Modirzadeh, and Gabriella Blum. War-Algorithm Accountability. Harvard Law School Program on International Law and Armed Conflict, 2016. http://dx.doi.org/10.54813/fltl8789.

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In War-Algorithm Accountability (August 2016), we introduce a new concept—war algorithms—that elevates algorithmically-derived “choices” and “decisions” to a, and perhaps the, central concern regarding technical autonomy in war. We thereby aim to shed light on and recast the discussion regarding “autonomous weapon systems” (AWS). We define “war algorithm” as any algorithm that is expressed in computer code, that is effectuated through a constructed system, and that is capable of operating in relation to armed conflict. In introducing this concept, our foundational technological concern is the
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