Gotowe bibliografie tematyczne / Robot sensing

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  1. Artykuły w czasopismach
  2. Rozprawy doktorskie
  3. Książki
  4. Części książek
  5. Streszczenia konferencji
  6. Raporty organizacyjne

Gotowa bibliografia na temat „Robot sensing”

Autor: Grafiati
Data publikacji: 2 czerwca 2025
Data aktualizacji: 31 lipca 2025

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Artykuły w czasopismach na temat "Robot sensing"

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Hayashi, Akiyoshi, Liz Katherine Rincon-Ardila, and Gentiane Venture. "Improving HRI with Force Sensing." Machines 10, no. 1 (2021): 15. http://dx.doi.org/10.3390/machines10010015.

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In the future, in a society where robots and humans live together, HRI is an important field of research. While most human–robot-interaction (HRI) studies focus on appearance and dialogue, touch-communication has not been the focus of many studies despite the importance of its role in human–human communication. This paper investigates how and where humans touch an inorganic non-zoomorphic robot arm. Based on these results, we install touch sensors on the robot arm and conduct experiments to collect data of users’ impressions towards the robot when touching it. Our results suggest two main thin
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Zou, Rui, Yubin Liu, Ying Li, Guoqing Chu, Jie Zhao, and Hegao Cai. "A Novel Human Intention Prediction Approach Based on Fuzzy Rules through Wearable Sensing in Human–Robot Handover." Biomimetics 8, no. 4 (2023): 358. http://dx.doi.org/10.3390/biomimetics8040358.

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With the use of collaborative robots in intelligent manufacturing, human–robot interaction has become more important in human–robot collaborations. Human–robot handover has a huge impact on human–robot interaction. For current research on human–robot handover, special attention is paid to robot path planning and motion control during the handover process; seldom is research focused on human handover intentions. However, enabling robots to predict human handover intentions is important for improving the efficiency of object handover. To enable robots to predict human handover intentions, a nove
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Yu, Xinbo, Shuang Zhang, Yu Liu, Bin Li, Yinsong Ma, and Gaochen Min. "Co-carrying an object by robot in cooperation with humans using visual and force sensing." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 379, no. 2207 (2021): 20200373. http://dx.doi.org/10.1098/rsta.2020.0373.

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Human–robot collaboration poses many challenges where humans and robots work inside a shared workspace. Robots collaborating with humans indirectly bring difficulties for accomplishing co-carrying tasks. In our work, we focus on co-carrying an object by robots in cooperation with humans using visual and force sensing. A framework using visual and force sensing is proposed for human–robot co-carrying tasks, enabling robots to actively cooperate with humans and reduce human efforts. Visual sensing for perceiving human motion is involved in admittance-based force control, and a hybrid controller
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Lapusan, Ciprian, Olimpiu Hancu, and Ciprian Rad. "Shape Sensing of Hyper-Redundant Robots Using an AHRS IMU Sensor Network." Sensors 22, no. 1 (2022): 373. http://dx.doi.org/10.3390/s22010373.

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The paper proposes a novel approach for shape sensing of hyper-redundant robots based on an AHRS IMU sensor network embedded into the structure of the robot. The proposed approach uses the data from the sensor network to directly calculate the kinematic parameters of the robot in modules operational space reducing thus the computational time and facilitating implementation of advanced real-time feedback system for shape sensing. In the paper the method is applied for shape sensing and pose estimation of an articulated joint-based hyper-redundant robot with identical 2-DoF modules serially conn
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Verner, Igor M., Dan Cuperman, and Michael Reitman. "Exploring Robot Connectivity and Collaborative Sensing in a High-School Enrichment Program." Robotics 10, no. 1 (2021): 13. http://dx.doi.org/10.3390/robotics10010013.

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Education is facing challenges to keep pace with the widespread introduction of robots and digital technologies in industry and everyday life. These challenges necessitate new approaches to impart students at all levels of education with the knowledge of smart connected robot systems. This paper presents the high-school enrichment program Intelligent Robotics and Smart Transportation, which implements an approach to teaching the concepts and skills of robot connectivity, collaborative sensing, and artificial intelligence, through practice with multi-robot systems. The students used a simple co
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Verner, Igor M., Dan Cuperman, and Michael Reitman. "Exploring Robot Connectivity and Collaborative Sensing in a High-School Enrichment Program." Robotics 10, no. 1 (2021): 13. http://dx.doi.org/10.3390/robotics10010013.

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Education is facing challenges to keep pace with the widespread introduction of robots and digital technologies in industry and everyday life. These challenges necessitate new approaches to impart students at all levels of education with the knowledge of smart connected robot systems. This paper presents the high-school enrichment program Intelligent Robotics and Smart Transportation, which implements an approach to teaching the concepts and skills of robot connectivity, collaborative sensing, and artificial intelligence, through practice with multi-robot systems. The students used a simple co
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Bogue, Robert. "Detecting humans in the robot workspace." Industrial Robot: An International Journal 44, no. 6 (2017): 689–94. http://dx.doi.org/10.1108/ir-07-2017-0132.

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Purpose This paper aims to provide a technical insight into a selection of robotic people detection technologies and applications. Design/methodology/approach Following an introduction, this paper first discusses people-sensing technologies which seek to extend the capabilities of human-robot collaboration by allowing humans to operate alongside conventional, industrial robots. It then provides examples of developments in people detection and tracking in unstructured, dynamic environments. Developments in people sensing and monitoring by assistive robots are then considered and finally, brief
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Giunchiglia, Fausto, Enrico Bignotti, and Mattia Zeni. "Human-Like Context Sensing for Robot Surveillance." International Journal of Semantic Computing 12, no. 01 (2018): 129–48. http://dx.doi.org/10.1142/s1793351x1840007x.

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Robot surveillance requires robots to make sense of what is happening around them, which is what humans do with contexts. This is critical when the robots have to interact with people. Thus, the main issue is how to model human-like context to be mapped to robots, so that they can mirror human understanding. We propose a context model, organized according to the different dimensions of the environment. We then introduce the notions of endurants and perdurants to account for how space and time, respectively, aggregate context for humans. To map real-world data, i.e. sensory inputs, to our conte
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Rogelio Guadarrama Olvera, J., Emmanuel Dean Leon, Florian Bergner, and Gordon Cheng. "Plantar Tactile Feedback for Biped Balance and Locomotion on Unknown Terrain." International Journal of Humanoid Robotics 17, no. 01 (2020): 1950036. http://dx.doi.org/10.1142/s0219843619500361.

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This work introduces a new sensing system for biped robots based on plantar robot skin, which provides not only the resultant forces applied on the ankles but a precise shape of the pressure distribution in the sole together with other extra sensing modalities (temperature, pre-touch and acceleration). The information provided by the plantar robot skin can be used to compute the center of pressure and the ground reaction forces. This information also enables the online construction of the supporting polygon and its preemptive shape before foot landing using the proximity sensors in the robot s
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Pearson, Martin J., Ben Mitchinson, J. Charles Sullivan, Anthony G. Pipe, and Tony J. Prescott. "Biomimetic vibrissal sensing for robots." Philosophical Transactions of the Royal Society B: Biological Sciences 366, no. 1581 (2011): 3085–96. http://dx.doi.org/10.1098/rstb.2011.0164.

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Active vibrissal touch can be used to replace or to supplement sensory systems such as computer vision and, therefore, improve the sensory capacity of mobile robots. This paper describes how arrays of whisker-like touch sensors have been incorporated onto mobile robot platforms taking inspiration from biology for their morphology and control. There were two motivations for this work: first, to build a physical platform on which to model, and therefore test, recent neuroethological hypotheses about vibrissal touch; second, to exploit the control strategies and morphology observed in the biologi
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Rozprawy doktorskie na temat "Robot sensing"

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Kochekali, Homayun. "Force sensing enhancement of robot system." Thesis, Middlesex University, 1991. http://eprints.mdx.ac.uk/13488/.

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At present there is a general industrial need to improve robot performance. Force feedback, which involves sensing and actuation, is one means of improving the relative position between the workpiece and the end-effector. In this research work various causes of errors and poor robot performance are identified. Several methods of improving the performance of robotic systems are discussed. As a result of this research, a system was developed which is interposed between the wrist and the gripper of the manipulator. This system integrates a force sensor with a micro-manipulator, via an electronic
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Leonard, John J. "Directed sonar sensing for mobile robot navigation." Thesis, University of Oxford, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.260128.

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Philpott, M. L. "Direct arc sensing for robot MIG welding." Thesis, Cranfield University, 1986. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.376205.

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Long, Xianchao. "Tactile-Based Mobile Robot Navigation." Digital WPI, 2013. https://digitalcommons.wpi.edu/etd-theses/891.

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"This thesis presents an effective approach to study tactile based mobile robot navigation. A Matlab simulator, which can simulate the properties of the tactile sensors, the environment, and the motion of the robot, is developed. The simulator uses an abstraction model of a compliant tactile sensor to represent an array of sensors covering the robot. The tactile sensor can detect normal and shear forces. The simulator has been used by a set of human subjects to drive a robot in an indoor environment to capture data. The details of the implementation and the data collected are presented in this
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Chen, Ning. "Tactile sensing and direct touch-driven robot control." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/nq21556.pdf.

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Wijesoma, Wijerupage Sardha. "Robot control using joint and end-effector sensing." Thesis, University of Cambridge, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.279587.

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Craver, Matthew David. "Mobile Robot Homing Control Based on Odor Sensing." Thesis, North Carolina State University, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=3690207.

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Sanchez, Loza Jose Manuel. "Shape sensing of deformable objects for robot manipulation." Thesis, Université Clermont Auvergne‎ (2017-2020), 2019. http://www.theses.fr/2019CLFAC012/document.

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Les objets déformables sont omniprésents dans notre vie quotidienne. Chaque jour, nous manipulons des vêtements dans des configurations innombrables pour nous habiller, nouons les lacets de nos chaussures, cueillons des fruits et des légumes sans les endommager pour notre consommation et plions les reçus dans nos portefeuilles. Toutes ces tâches impliquent de manipuler des objets déformables et peuvent être exécutées sans problème par une personne. Toutefois, les robots n'ont pas encore atteint le même niveau de dextérité. Contrairement aux objets rigides, que les robots sont maintenant capabl
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Mehdian, Mehrdad. "Tactile sensing for automata and prosthesis." Thesis, University of Greenwich, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.280490.

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Li, Youfu. "Robot proximity sensing and a strategy for transition control." Thesis, University of Oxford, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.334263.

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Książki na temat "Robot sensing"

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Kochekali, Homayun. Force sensing enhancement of robot system. Middlesex Polytechnic, 1991.

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Morik, Katharina. Making Robots Smarter: Combining Sensing and Action Through Robot Learning. Springer US, 1999.

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Katharina, Morik, Kaiser Michael, and Klingspor Volker, eds. Making robots smarter: Combining sensing and action through robot learning. Kluwer Academic, 1999.

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Leonard, John J., and Hugh F. Durrant-Whyte. Directed Sonar Sensing for Mobile Robot Navigation. Springer US, 1992. http://dx.doi.org/10.1007/978-1-4615-3652-9.

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Leonard, John J. Directed Sonar Sensing for Mobile Robot Navigation. Springer US, 1992.

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1961-, Durrant-Whyte Hugh F., ed. Directed sonar sensing for mobile robot navigation. Kluwer Academic Publishers, 1992.

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Luk, Bing Lam. Robot force sensing using stochastic monitoring of the actuator current. Portsmouth Polytechnic, School of Systems Engineering, 1991.

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Center, Langley Research, ed. Robot position sensor fault tolerance. National Aeronautics and Space Administration, Langley Research Center, 1997.

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Kyojiro, Kakomori, and United States. National Aeronautics and Space Administration., eds. Dynamic sensing of 6-axis external force and moment applied to a robot end. National Aeronautics and Space Administration, 1987.

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Jer-Nan, Juang, and Langley Research Center, eds. Experimental robot position sensor fault tolerance using accelerometers and joint torque sensors. National Aeronautics and Space Administration, Langley Research Center, 1997.

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Części książek na temat "Robot sensing"

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Cumbers, David. "External sensing: tactile sensors." In Robot Technology Workbook. Macmillan Education UK, 1993. http://dx.doi.org/10.1007/978-1-349-12688-0_12.

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Cumbers, David. "External sensing: vision sensors." In Robot Technology Workbook. Macmillan Education UK, 1993. http://dx.doi.org/10.1007/978-1-349-12688-0_13.

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Miller, Richard K. "Grippers and Tactile Sensing." In Industrial Robot Handbook. Springer US, 1989. http://dx.doi.org/10.1007/978-1-4684-6608-9_3.

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Todd, D. J. "Sensing for Robots." In Fundamentals of Robot Technology. Springer Netherlands, 1986. http://dx.doi.org/10.1007/978-94-011-6768-0_5.

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Fearing, Ronald S. "Tactile Sensing for Shape Interpretation." In Dextrous Robot Hands. Springer New York, 1990. http://dx.doi.org/10.1007/978-1-4613-8974-3_10.

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Guo, Tongying, Hui Zhang, and Lincang Zhu. "Sensing Technology for Special Robots." In Special Robot Technology. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0589-8_3.

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Grant, E. "Uncertainty in Robot Sensing." In Sensor-Based Robots: Algorithms and Architectures. Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-75530-9_3.

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Kriegman, David J., Ernst Triendl, and Thomas O. Binford. "A Mobile Robot: Sensing, Planning and Locomotion." In Autonomous Robot Vehicles. Springer New York, 1990. http://dx.doi.org/10.1007/978-1-4613-8997-2_33.

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Leonard, John J., and Hugh F. Durrant-Whyte. "Directed Sensing Strategies." In Directed Sonar Sensing for Mobile Robot Navigation. Springer US, 1992. http://dx.doi.org/10.1007/978-1-4615-3652-9_6.

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Liu, Honghai, Zhaojie Ju, Xiaofei Ji, Chee Seng Chan, and Mehdi Khoury. "Fuzzy Qualitative Robot Kinematics." In Human Motion Sensing and Recognition. Springer Berlin Heidelberg, 2017. http://dx.doi.org/10.1007/978-3-662-53692-6_3.

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Streszczenia konferencji na temat "Robot sensing"

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Qafko, Tedi, Patrick Blanchard, Quang Vu, and Federica Aveta. "Object Tracking Spherical Underwater Sensing Robot." In 2024 IEEE 15th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON). IEEE, 2024. http://dx.doi.org/10.1109/uemcon62879.2024.10754667.

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Zhang, Yang, Hao Wu, Peng Li, Deen Bai, Shuai Guo, and Chaoquan Tang. "Design of Haptic Sensing Snake Robot." In 2024 7th International Conference on Robotics, Control and Automation Engineering (RCAE). IEEE, 2024. https://doi.org/10.1109/rcae62637.2024.10834230.

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Dhivya, P., V. G. Karthiga, S. Vinotha, S. Saravanakumar, T. Abinith, and T. Varunsri. "Advanced Sensing and Actuation Health Monitoring Robot." In 2024 5th International Conference on Electronics and Sustainable Communication Systems (ICESC). IEEE, 2024. http://dx.doi.org/10.1109/icesc60852.2024.10689853.

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Yuan, Ying, Haichuan Che, Yuzhe Qin, et al. "Robot Synesthesia: In-Hand Manipulation with Visuotactile Sensing." In 2024 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2024. http://dx.doi.org/10.1109/icra57147.2024.10610532.

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Rajesh, P., A. Sai Kumar, T. K. Manisha Sarayu, A. Durga Prasad, and Ch Sai Dhanush. "Path Traversal and Obstacle Sensing Robot using Arduino." In 2023 Second IEEE International Conference on Measurement, Instrumentation, Control and Automation (ICMICA). IEEE, 2024. http://dx.doi.org/10.1109/icmica61068.2024.10732361.

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Antunes, Rodrigo, Luan Lang, Martim Lima de Aguiar, Thiago Assis Dutra, Pedro Dinis Gaspar, and Nuno José Matos Pereira. "Self-Sensing Soft Finger Produced from Conductive TPU for Adaptive Grasping and Force Sensing Applications." In 2025 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC). IEEE, 2025. https://doi.org/10.1109/icarsc65809.2025.10970182.

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Qian, Binsen, and Harry H. Cheng. "Extending Educational Robot Sensing Capabilities Through Equipping an External Microcontroller." In ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/detc2019-98470.

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Abstract The popularity of the educational robot in K-12 classroom has dramatically increased in the past decades to engage students studying not only Science, Technology, Engineering and Mathematics (STEM), but also 21st-century skills. Most educational robots tend to be as simple as possible such that the lower grades can benefit from the robotics technologies safely. However, such design consideration makes most educational robots with none or minimal sensing capabilities. However, it is very important for senior students to learn more advanced robotics concepts and applications. This paper
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Qiao, Guixiu, and Guangkun Li. "Auto-Calibration for Vision-Based 6-D Sensing System to Support Monitoring and Health Management for Industrial Robots." In ASME 2021 16th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/msec2021-63892.

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Abstract Industrial robots play important roles in manufacturing automation for smart manufacturing. Some high-precision applications, for example, robot drilling, robot machining, robot high-precision assembly, and robot inspection, require higher robot accuracy compared with traditional part handling operations. The monitoring and assessment of robot accuracy degradation become critical for these applications. A novel vision-based sensing system for 6-D measurement (six-dimensional x, y, z, yaw, pitch, and roll) is developed at the National Institute of Standards and Technology (NIST) to mea
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Qiao, Guixiu, and Brian A. Weiss. "Monitoring, Diagnostics, and Prognostics for Robot Tool Center Accuracy Degradation." In ASME 2018 13th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/msec2018-6603.

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Over time, robots degrade because of age and wear, leading to decreased reliability and increasing potential for faults and failures; this negatively impacts robot availability. Economic factors motivate facilities and factories to improve maintenance operations to monitor robot degradation and detect faults and failures, especially to eliminate unexpected shutdowns. Since robot systems are complex, with sub-systems and components, it is challenging to determine these constituent elements’ specific influence on the overall system performance. The development of monitoring, diagnostic, and prog
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Christensen, Henrik I. "AUC robot camera head." In Aerospace Sensing, edited by Kevin W. Bowyer. SPIE, 1992. http://dx.doi.org/10.1117/12.58560.

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Raporty organizacyjne na temat "Robot sensing"

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Brock, D. L. Contact sensing palm for the Salisbury robot hand. Office of Scientific and Technical Information (OSTI), 1990. http://dx.doi.org/10.2172/6529634.

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Latombe, J. C., A. Lazanas, and S. Shekhar. Robot Motion Planning with Uncertainty in Control and Sensing. Defense Technical Information Center, 1989. http://dx.doi.org/10.21236/ada323613.

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Bostelman, Roger. Electrical design of the infraredultrasonic sensing for a robot gripper. National Institute of Standards and Technology, 1989. http://dx.doi.org/10.6028/nist.ir.89-4223.

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Edsinger-Gonzales, Aaron. Design of a Compliant and Force Sensing Hand for a Humanoid Robot. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada434151.

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Xavier, P. G., R. G. Brown, and P. A. Watterberg. Coordinating robot motion, sensing, and control in plans. LDRD project final report. Office of Scientific and Technical Information (OSTI), 1997. http://dx.doi.org/10.2172/527563.

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Spelt, P. F., and H. W. Harvey. Enhanced control & sensing for the REMOTEC ANDROS Mk VI robot. Final report. Office of Scientific and Technical Information (OSTI), 1997. http://dx.doi.org/10.2172/508111.

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Spelt, P. F., and H. W. Harvey. Enhanced control and sensing for the REMOTEC ANDROS Mk VI robot. CRADA final report. Office of Scientific and Technical Information (OSTI), 1998. http://dx.doi.org/10.2172/661618.

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Haas, Gary, and Philip R. Osteen. Wall Sensing for an Autonomous Robot With a Three-Dimensional Time-of-Flight (3-D TOF) Camera. Defense Technical Information Center, 2011. http://dx.doi.org/10.21236/ada539897.

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Ray, Laura, Madeleine Jordan, Steven Arcone, et al. Velocity field in the McMurdo shear zone from annual ground penetrating radar imaging and crevasse matching. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/42623.

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The McMurdo shear zone (MSZ) is strip of heavily crevassed ice oriented in the south-north direction and moving northward. Previous airborne surveys revealed a chaotic crevasse structure superimposed on a set of expected crevasse orientations at 45 degrees to the south-north flow (due to shear stress mechanisms). The dynamics that produced this chaotic structure are poorly understood. Our purpose is to present our field methodology and provide field data that will enable validation of models of the MSZ evolution, and here, we present a method for deriving a local velocity field from ground pen
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Gart, Sean, Mark Bundy, and Raymond Vonwahlde. 2022 MRC-ARL Summer Student Team Research Experience – Air Deployed Robots for Mobile Sensing. DEVCOM Army Research Laboratory, 2023. http://dx.doi.org/10.21236/ad1211732.

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