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Relevant bibliographies by topics / Intelligent robotic control systems

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Academic literature on the topic 'Intelligent robotic control systems'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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Journal articles on the topic "Intelligent robotic control systems"

1

Buxbaum, Hans-Jürgen. "Intelligent robotic planning systems." Control Engineering Practice 5, no. 8 (1997): 1183. http://dx.doi.org/10.1016/s0967-0661(97)90040-x.

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Romanov, Aleksey M. "A review on control systems hardware and software for robots of various scale and purpose. Part 2. Service robotics." Russian Technological Journal 7, no. 6 (2020): 68–86. http://dx.doi.org/10.32362/2500-316x-2019-7-6-68-86.

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A review of robotic systems was carried out. The paper analyzes applied hardware and software solutions and summarizes the most common block diagrams of control systems. The analysis of approaches to control systems scaling, the use of intelligent control, the achievement of fault tolerance, and the reduction of the weight and size of control system elements belonging to various classes of robotic systems were carried out. The goal of the review is finding common approaches used in various areas of robotics to build on their basis a uniform methodology for designing scalable intelligent contro

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Cichon, Torben, Marc Priggemeyer, and Jürgen Rossmann. "Simulation-Based Control and Simulation-Based Support in eRobotics Applications." Applied Mechanics and Materials 840 (June 2016): 74–81. http://dx.doi.org/10.4028/www.scientific.net/amm.840.74.

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The utilization of simulation capabilities in the development process of robotic systems is already known as one standard procedure for predicting complex system behavior in a time- and cost efficient manner. eRobotics join multiple process simulation components to build "Virtual Testbeds" to provide a comprehensive tool chain and thus a holistic development. VTB may represent "mental models" of robotic systems and their environment. Therefore, they allow the development of control schemes and directly transfer simulation results for Simulation-based Control for implementing intelligent robot

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Zaitceva, Iuliia, and Boris Andrievsky. "Methods of Intelligent Control in Mechatronics and Robotic Engineering: A Survey." Electronics 11, no. 15 (2022): 2443. http://dx.doi.org/10.3390/electronics11152443.

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Artificial intelligence is becoming an increasingly popular tool in more and more areas of technology. New challenges in control systems design and application are related to increased productivity, control flexibility, and processing of big data. Some kinds of systems require autonomy in real-time decision-making, while the other ones may serve as an essential factor in human-robot interaction and human influences on system performance. Naturally, the complex tasks of controlling technical systems require new modern solutions, but there remains an inextricable link between control theory and

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MAEDER, ANDREAS, HANNES BISTRY, and JIANWEI ZHANG. "INTELLIGENT VISION SYSTEMS FOR ROBOTIC APPLICATIONS." International Journal of Information Acquisition 05, no. 03 (2008): 259–67. http://dx.doi.org/10.1142/s0219878908001648.

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Vision-based sensors are a key component for robot-systems, where many tasks depend on image data. Realtime control constraints bind a lot of processing power for only a single sensor modality. Dedicated and distributed processing resources are the "natural" solution to overcome this limitation. This paper presents experiments, using embedded processors as well as dedicated hardware, to execute various image (pre)processing tasks. Architectural concepts and requirements for intelligent vision systems have been acquired.

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Wilson, Callum, Francesco Marchetti, Marilena Di Carlo, Annalisa Riccardi, and Edmondo Minisci. "Classifying Intelligence in Machines: A Taxonomy of Intelligent Control." Robotics 9, no. 3 (2020): 64. http://dx.doi.org/10.3390/robotics9030064.

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The quest to create machines that can solve problems as humans do leads us to intelligent control. This field encompasses control systems that can adapt to changes and learn to improve their actions—traits typically associated with human intelligence. In this work we seek to determine how intelligent these classes of control systems are by quantifying their level of adaptability and learning. First we describe the stages of development towards intelligent control and present a definition based on literature. Based on the key elements of this definition, we propose a novel taxonomy of intellige

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HUTSA, O., D. YELCHANINOV, D. YANUSHKEVYCH, et al. "Conceptualization of Intelligent Control System for Humanitarian Demining Robotic Complexes Based on Verbal Methods." Science and Innovation 20, no. 3 (2024): 82–95. http://dx.doi.org/10.15407/scine20.03.082.

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Introduction. Humanitarian demining is characterized by growing attention to the problems of creating and using robotic systems. The most important aspect of their use is the control method.Problem Statement. At present, the fi rst generation robotic complexes (controlled devices) have been the mostcommon, the second generation complexes (semi-autonomous devices) have been improving. To switch to the third generation complexes (autonomous devices), it is necessary to develop intelligent control systems based on artificial intelligence technologies. The most used for system development are quan

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Priyanka, Das. "Integrating Advanced Control Strategies for Enhanced Motor Efficiency in Robotics." INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH AND CREATIVE TECHNOLOGY 10, no. 6 (2024): 1–5. https://doi.org/10.5281/zenodo.14631891.

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Motor efficiency requires diversified paradigm integration to facilitate the advancement of robotics applications through precision, energy optimization, and reliability. Advanced control strategies like AI-driven predictive mechanisms, harmonic drive systems, and real-time feedback tools in motor performance underline the efficiency required in robotic technologies. As a collective role for robotic motors, the approaches enable precise torque and speed modulation, dynamic adaptability to environmental changes, and energy-efficient operation in controlled strategies. Understanding theoretical

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Romanov, A. M. "A review on control systems hardware and software for robots of various scale and purpose. Part 1. Industrial robotics." Russian Technological Journal 7, no. 5 (2019): 30–46. http://dx.doi.org/10.32362/2500-316x-2019-7-5-30-46.

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A review of robotic systems is presented. The paper analyzes applied hardware and software solutions and summarizes the most common block diagrams of control systems. The analysis of approaches to control systems scaling, the use of intelligent control, achieving fault tolerance, reducing the weight and size of control system elements belonging to various classes of robotic systems is carried out. The goal of the review is finding common approaches used in various areas of robotics to build on their basis a uniform methodology for designing scalable intelligent control systems for robots with

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Ahmad Shauri, Ruhizan Liza, and Ahmad Badiuzzaman Roslan. "Non-Intelligent and Intelligent Force Control for Robotic Applications: A Review." ASM Science Journal 16 (November 5, 2021): 1–13. http://dx.doi.org/10.32802/asmscj.2021.806.

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This paper presents an overview of force control approaches for robotic systems. It covers three main methods: non-intelligent methods, intelligent methods, and recent methods. In each section, the discussion focused on how the researcher implements their methods in control system to obtain the desired force control for system’s robustness towards external disturbances and internal uncertainties. The purpose of applying force control is to ensure that the executed robotic task does not damage the manipulated object or environment. The benefits for each method were highlighted at the end of eac

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Dissertations / Theses on the topic "Intelligent robotic control systems"

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Zaiuddin, Syed Muhammad. "Intelligent control schemes for single and multiple arm robotic systems." Thesis, University of Sheffield, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.319447.

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Ma, Yu-xu Lecky. "Discrete iterative learning control of robotic manipulators /." [Hong Kong : University of Hong Kong], 1991. http://sunzi.lib.hku.hk/hkuto/record.jsp?B13142896.

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Sillitoe, Ian P. W. "Plethora : a framework for the intelligent control of robotic assembly systems." Thesis, Loughborough University, 1992. https://dspace.lboro.ac.uk/2134/26146.

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The thesis describes a distributed software environment designed for the development, evaluation and comparison of new techniques in knowledge based control of robot assembly work cells. It has characteristics which fulfil deficiencies within previous systems and contains within it new techniques in task specification, distributed control[1,2], object recognition[3,4] and path planning[5]. The control of the resources within the cell is based upon an extension of the facilities of a classical blackboard architecture to include plan execution. Unlike previous schemes, these additions allow Plet

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馬裕旭 and Yu-xu Lecky Ma. "Discrete iterative learning control of robotic manipulators." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1991. http://hub.hku.hk/bib/B31232723.

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Karakaşoğlu, Ahmet 1961. "Design of a rule-based control system for decentralized adaptive control of robotic manipulators." Thesis, The University of Arizona, 1988. http://hdl.handle.net/10150/276874.

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This thesis is concerned with the applicability of model reference adaptive control to the control of robot manipulators under a wide range of configuration and payload changes, and a comparison of the performance of this technique with that of the non-adaptive schemes. The dynamic equations of robot manipulators are highly nonlinear and are difficult to determine precisely. For these reasons there is an interest in applying adaptive control techniques to robot manipulators. In this work, the detailed performance of three adaptive controllers are studied and compared with that of a non-adaptiv

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Sutherland, Alistair James. "A torso driven walking algorithm for dynamically balanced variable speed biped robots." University of Western Australia. School of Electrical, Electronic and Computer Engineering, 2007. http://theses.library.uwa.edu.au/adt-WU2007.0049.

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As a contribution toward the objective of developing useful walking machines, this dissertation considers solutions to some of the problems involved with bipedal robot development. The main area of focus involves control system design and implementation for dynamically balanced walking robots. A new algorithm “Torso Driven Walking” is presented, which reduces the complexity of the control problem to that of balancing the robot’s torso. All other aspects of the system are indirectly controlled by the changing robot state resulting from direct control of the robot’s torso. The result is literall

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GHAFFARI, MASOUD. "PERCEPTION-BASED CONTROL FOR INTELLIGENT SYSTEMS." University of Cincinnati / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1155739459.

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Mellodge, Patricia. "Feedback Control for a Path Following Robotic Car." Thesis, Virginia Tech, 2002. http://hdl.handle.net/10919/32100.

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This thesis describes the current state of development of the Flexible Low-cost Automated Scaled Highway (FLASH) laboratory at the Virginia Tech Transportation Institute (VTTI). The FLASH lab and the scale model cars contained therein provide a testbed for the small scale development stage of intelligent transportation systems (ITS). In addition, the FLASH lab serves as a home to the prototype display being developed for an educational museum exhibit. This thesis also gives details of the path following lateral controller implemented on the FLASH car. The controller was developed using the

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Ngan, Choi-chik, and 顔才績. "A hidden Markov model approach to force-based contact recognition for intelligent robotic assembly." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2002. http://hub.hku.hk/bib/B31243496.

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Liu, Yukang. "Virtualized Welding Based Learning of Human Welder Behaviors for Intelligent Robotic Welding." UKnowledge, 2014. http://uknowledge.uky.edu/ece_etds/51.

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Combining human welder (with intelligence and sensing versatility) and automated welding robots (with precision and consistency) can lead to next generation intelligent welding systems. In this dissertation intelligent welding robots are developed by process modeling / control method and learning the human welder behavior. Weld penetration and 3D weld pool surface are first accurately controlled for an automated Gas Tungsten Arc Welding (GTAW) machine. Closed-form model predictive control (MPC) algorithm is derived for real-time welding applications. Skilled welder response to 3D weld pool sur

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Books on the topic "Intelligent robotic control systems"

1

Katic, Dusko. Intelligent Control of Robotic Systems. Springer Netherlands, 2003.

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Katic, Dusko, and Miomir Vukobratovic. Intelligent Control of Robotic Systems. Springer Netherlands, 2003. http://dx.doi.org/10.1007/978-94-017-0317-8.

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Miomir, Vukobratović, ed. Intelligent control of robotic systems. Kluwer Academic Publishers, 2003.

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4

Liu, Dikai, Lingfeng Wang, and Kay Chen Tan, eds. Design and Control of Intelligent Robotic Systems. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-89933-4.

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Liu, Jiming. Multi-agent robotic systems. CRC Press, 2001.

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A, Desrochers A., ed. Intelligent robotic systems for space exploration. Kluwer Academic Publishers, 1992.

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Jain, Lakhmi C. Soft Computing for Intelligent Robotic Systems. Physica-Verlag HD, 1998.

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NATO Advanced Research Workshop on Highly Redundant Sensing in Robotic Systems (1988 Il Ciocco, Italy). Highly redundant sensing in robotic systems. Springer-Verlag, 1990.

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Nayak, Nitin. Intelligent seam tracking for robotic welding. Springer-Verlag, 1993.

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International, Conference on Intelligent Autonomous Systems (7th 2002 Marina del Rey Calif ). Intelligent autonomous systems 7. IOS Press, 2002.

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Book chapters on the topic "Intelligent robotic control systems"

1

Katic, Dusko, and Miomir Vukobratovic. "Intelligent Control in Contemporary Robotics." In Intelligent Control of Robotic Systems. Springer Netherlands, 2003. http://dx.doi.org/10.1007/978-94-017-0317-8_1.

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Doulgeri, Zoe, and Giuseppe D’Alessandro. "Development of Intelligent Control for Robot Cells using Knowledge Based Simulation." In Robotic Systems. Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-011-2526-0_68.

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Castillo, Oscar, and Patricia Melin. "Intelligent Control of Robotic Dynamic Systems." In Soft Computing for Control of Non-Linear Dynamical Systems. Physica-Verlag HD, 2001. http://dx.doi.org/10.1007/978-3-7908-1832-1_9.

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Katic, Dusko, and Miomir Vukobratovic. "Hybrid Intelligent Approaches in Robotics." In Intelligent Control of Robotic Systems. Springer Netherlands, 2003. http://dx.doi.org/10.1007/978-94-017-0317-8_5.

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Hamano, Fumio. "Intelligent Control." In Expert Systems and Robotics. Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-76465-3_45.

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Katic, Dusko, and Miomir Vukobratovic. "Examples of Intelligent Techniques for Robotic Applications." In Intelligent Control of Robotic Systems. Springer Netherlands, 2003. http://dx.doi.org/10.1007/978-94-017-0317-8_8.

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Katic, Dusko, and Miomir Vukobratovic. "Genetic Algorithms in Robotics." In Intelligent Control of Robotic Systems. Springer Netherlands, 2003. http://dx.doi.org/10.1007/978-94-017-0317-8_4.

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Vinogradov, Gennady P. "Patterns in Intelligent Control Systems for Robotic Systems." In Studies in Systems, Decision and Control. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-68172-2_2.

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Katic, Dusko, and Miomir Vukobratovic. "Neural Network Approach in Robotics." In Intelligent Control of Robotic Systems. Springer Netherlands, 2003. http://dx.doi.org/10.1007/978-94-017-0317-8_2.

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Katic, Dusko, and Miomir Vukobratovic. "Fuzzy Logic Approach in Robotics." In Intelligent Control of Robotic Systems. Springer Netherlands, 2003. http://dx.doi.org/10.1007/978-94-017-0317-8_3.

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Conference papers on the topic "Intelligent robotic control systems"

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Stepanova, Anastasiia, Ha Pham, and Alireza Zourmand. "AI-Augmented Robotic System for Agriculture: Intelligent Packing Application." In 2024 IEEE 12th Conference on Systems, Process & Control (ICSPC). IEEE, 2024. https://doi.org/10.1109/icspc63060.2024.10862972.

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Qiao, Yi, Ruochuan Shi, Fengrui Guo, et al. "A Hierarchical Intelligent Rehabilitation Robotic System Based on MI-EEG." In 2024 43rd Chinese Control Conference (CCC). IEEE, 2024. http://dx.doi.org/10.23919/ccc63176.2024.10662738.

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Liu, Weici, Runhao Huang, and Junjie Huang. "Research on control system of the robotic arm." In 4th International Conference on Mechatronics and Intelligent Control, edited by Yusri Yusof and Yinquan Yu. SPIE, 2025. https://doi.org/10.1117/12.3065879.

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Kececi, E. Faruk, and Gang Tao. "An Intelligent Robotic Walker: Mechanical Design and Control System." In ASME 2002 International Mechanical Engineering Congress and Exposition. ASMEDC, 2002. http://dx.doi.org/10.1115/imece2002-32665.

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This paper presents the mechanical and control system design of a mobile robot designed as a mobility aid for the elderly. Today, with advanced computer control and robotics technologies it is possible to design more intelligent robots, which can help elderly people in their dally life tasks. We have designed an intelligent robotic walker. The main functions of this advanced walker are: following its path with observed control, changing its structural shape to prevent unbalancing the user when walking on a slope, and braking to stop the user falling down. The base of the robot is considered an

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Akcadag, C., A. Shirkhodaie, and A. H. Soni. "Computer Control of a Flexible Robotic Cell." In ASME 1992 Design Technical Conferences. American Society of Mechanical Engineers, 1992. http://dx.doi.org/10.1115/detc1992-0450.

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Abstract Intelligent robotic systems require a tremendous flexibility and intelligence to execute complex tasks. To facilitate task planning of intelligent robots and integrate sensory information for on-line task monitoring, there is a need to establish a communication linkage between robot controller and human operator through a computer. This paper presents the design of a generic cell controller for intelligent planning and execution of robotic cell operations and for real-time task monitoring. This paper details the architecture of hardware and software developed for the control of a comm

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Trivedi, Mohan M. "Intelligent robotic systems: control and cooperation." In SPIE's 1995 Symposium on OE/Aerospace Sensing and Dual Use Photonics, edited by Bruno Bosacchi and James C. Bezdek. SPIE, 1995. http://dx.doi.org/10.1117/12.211795.

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Tsymbal, Oleksandr, and Oleksandr Mordyk. "Intelligent manipulation control for robotic system." In COMPUTER AND INFORMATION SYSTEMS AND TECHNOLOGIES. Press of the Kharkiv National University of Radioelectronics, 2020. http://dx.doi.org/10.30837/ivcsitic2020201374.

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Hadi, Alireza, Mohammad Elahinia, Asadollah Ghazavi, and Majid M. Moghadam. "Design, Modeling and Control of a New Robotic Module Actuated by Shape Memory Alloy Springs." In ASME 2009 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. ASMEDC, 2009. http://dx.doi.org/10.1115/smasis2009-1293.

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Modular robotic systems provide attractive benefits in the form of re-configurable robots that can change and adapt for special tasks. Self-reconfigurable is re-configurable robot with the ability to change their framework for different missions. One way to increase robots capabilities and to achieve self-configurable robots is to develop small, powerful and dexterous modules. In this paper, a new mechanism which uses Shape Memory Alloy (SMA) spring actuators is applied to develop a robotic module. Among the proposed modular systems until now, shape memory alloys especially the spring type are

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Xiao, Mingbo, Sunan Huang, and Qing-Chang Zhong. "Intelligent fault diagnosis for robotic systems." In 2014 11th IEEE International Conference on Control & Automation (ICCA). IEEE, 2014. http://dx.doi.org/10.1109/icca.2014.6871072.

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Portillo-Velez, Rogelio de J., Alejandro Rodriguez-Angeles, and Carlos A. Cruz-Villar. "Computing Independent Contact Regions for Robotic Grasping." In Intelligent Systems and Control. ACTAPRESS, 2011. http://dx.doi.org/10.2316/p.2011.744-091.

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Reports on the topic "Intelligent robotic control systems"

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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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Yoozbashizadeh, Mahdi, and Forouzan Golshani. Robotic Parking Technology for Congestion Mitigation and Air Quality Control Around Park & Rides. Mineta Transportation Institute, 2021. http://dx.doi.org/10.31979/mti.2021.1936.

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A lack or limited availability for parking may have multiple consequences, not the least of which is driver frustration, congestion, and air pollution. However, there is a greater problem that is not widely recognized by the public, namely the negative effect on the use of transit systems due to insufficient parking spaces close to key transit stations. Automated parking management systems, which have been successfully deployed in several European and Japanese cities, can manage parking needs at transit stations more effectively than other alternatives. Numerous studies have confirmed that qui

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Niles, Kenneth, Emily Leathers, Joe Tom, et al. Leveraging artificial intelligence and machine learning (AI/ML) for levee culvert Inspections in USACE Flood Control Systems (FCS). Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/49210.

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Levee inspections are essential in preventing flooding within populated regions. Risk assessments of structures are performed to identify potential failure modes to maintain the safety and health of the structure. The data collection and defect coding parts of the inspection process can be labor-intensive and time-consuming. The integration of machine learning (ML) and artificial intelligence (AI) techniques may increase accuracy of assessments and reduce time and cost. To develop a foundation for a fully autonomous inspection process, this research investigates methods to gather information f

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Morse, A. S. Intelligent Control of Uncertain Systems. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada375427.

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Ozcelik, Selahattin, and Michael Blackburn. Intelligent Control of a Highly Flexible Robotic Structure With Hundreds of Motor Elements. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada442046.

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Jannett, Thomas C. Intelligent Control for Future Autonomous Distributed Sensor Systems. Defense Technical Information Center, 2007. http://dx.doi.org/10.21236/ada468584.

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Quintero, Richard. A real-time control system methodology for developing intelligent control systems. National Institute of Standards and Technology, 1992. http://dx.doi.org/10.6028/nist.ir.4936.

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Chaudhary, Anil B. Intelligent Control Systems for Hot Forging and Extrusion Processes. Defense Technical Information Center, 1994. http://dx.doi.org/10.21236/ada411076.

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Mitter, Sanjoy K. Center for the Study of Intelligent Control Systems (Fellowships). Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/ada263604.

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Pertzborn, Amanda J., and Daniel A. Veronica. Baseline Control Systems in the Intelligent Building Agents Laboratory. National Institute of Standards and Technology, 2022. http://dx.doi.org/10.6028/nist.tn.2178.

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