Relevant bibliographies by topics / Object Detecting Sensors

Contents

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

Academic literature on the topic 'Object Detecting Sensors'

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

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Journal articles on the topic "Object Detecting Sensors"

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Jung, Sejung, Won Hee Lee, and Youkyung Han. "Change Detection of Building Objects in High-Resolution Single-Sensor and Multi-Sensor Imagery Considering the Sun and Sensor’s Elevation and Azimuth Angles." Remote Sensing 13, no. 18 (2021): 3660. http://dx.doi.org/10.3390/rs13183660.

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Building change detection is a critical field for monitoring artificial structures using high-resolution multitemporal images. However, relief displacement depending on the azimuth and elevation angles of the sensor causes numerous false alarms and misdetections of building changes. Therefore, this study proposes an effective object-based building change detection method that considers azimuth and elevation angles of sensors in high-resolution images. To this end, segmentation images were generated using a multiresolution technique from high-resolution images after which object-based building
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Jeong, Seonghark, Minseok Ko, and Jungha Kim. "LiDAR Localization by Removing Moveable Objects." Electronics 12, no. 22 (2023): 4659. http://dx.doi.org/10.3390/electronics12224659.

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In this study, we propose reliable Light Detection and Ranging (LiDAR) mapping and localization via the removal of moveable objects, which can cause noise for autonomous driving vehicles based on the Normal Distributions Transform (NDT). LiDAR measures the distances to objects such as parked and moving cars and objects on the road, calculating the time of flight required for the sensor’s beam to reflect off an object and return to the system. The proposed localization system uses LiDAR to implement mapping and matching for the surroundings of an autonomous vehicle. This localization is applied
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Yoon, Sungan, Ahmad Jalal, and Jeongho Cho. "MODAN: Multifocal Object Detection Associative Network for Maritime Horizon Surveillance." Journal of Marine Science and Engineering 11, no. 10 (2023): 1890. http://dx.doi.org/10.3390/jmse11101890.

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In maritime surveillance systems, object detection plays a crucial role in ensuring the security of nearby waters by tracking the movement of various objects, such as ships and aircrafts, that are found at sea, detecting illegal activities and preemptively countering or predicting potential risks. Using vision sensors such as cameras to monitor the sea can help to identify the shape, size, and color of objects, enabling the precise analysis of maritime situations. Additionally, vision sensors can monitor or track small ships that may escape radar detection. However, objects located at consider
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Rakesh, L., V. Priyanka, K. Pavan Kumar, N. Mahesh, and K. Sai Kiran. "Radar Based Object Detection using Ultrasonic Sensor." Journal of Remote Sensing GIS & Technology 8, no. 2 (2022): 7–14. http://dx.doi.org/10.46610/jorsgt.2022.v08i02.002.

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Aurdino-controlled radar is the subject of this project. A servo motor and an ultrasonic sensor are the essential components of this RADAR system. Components of the system primary role of the system is to detect something. Objects that fall within the specified parameters Ultrasonic sensors are built inside the servo motor. It rotates 180 degrees and uses software to show a visual representation. It's referred to as Processing IDE. A graphical representation of the data is provided by the Processing IDE. The angle or location of the object is also indicated, as well as its distance. This syste
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Reda, A. M., N. El-Sheimy, and A. Moussa. "DEEP LEARNING FOR OBJECT DETECTION USING RADAR DATA." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences X-1/W1-2023 (December 5, 2023): 657–64. http://dx.doi.org/10.5194/isprs-annals-x-1-w1-2023-657-2023.

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Abstract. Recently, Deep learning algorithms are becoming increasingly instrumental in autonomous driving by identifying and acknowledging road entities to ensure secure navigation and decision-making. Autonomous car datasets play a vital role in developing and evaluating perception systems. Nevertheless, the majority of current datasets are acquired using Light Detection and Ranging (LiDAR) and camera sensors. Utilizing deep neural networks yields remarkable outcomes in object recognition, especially when applied to analyze data from cameras and LiDAR sensors which perform poorly under advers
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Ma, Tian J., and Robert J. Anderson. "Remote Sensing Low Signal-to-Noise-Ratio Target Detection Enhancement." Sensors 23, no. 6 (2023): 3314. http://dx.doi.org/10.3390/s23063314.

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In real-time remote sensing application, frames of data are continuously flowing into the processing system. The capability of detecting objects of interest and tracking them as they move is crucial to many critical surveillance and monitoring missions. Detecting small objects using remote sensors is an ongoing, challenging problem. Since object(s) are located far away from the sensor, the target’s Signal-to-Noise-Ratio (SNR) is low. The Limit of Detection (LOD) for remote sensors is bounded by what is observable on each image frame. In this paper, we present a new method, a “Multi-frame Movin
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Hahn, Bongsu. "Research and Conceptual Design of Sensor Fusion for Object Detection in Dense Smoke Environments." Applied Sciences 12, no. 22 (2022): 11325. http://dx.doi.org/10.3390/app122211325.

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In this paper, we propose a conceptual framework for a sensor fusion system that can detect objects in a dense smoke environment with a visibility of less than 1 m. Based on the review of several articles, we determined that by using a single thermal IR camera, a single Frequency-Modulated Continuous-Wave (FMCW) radar, and multiple ultrasonic sensors simultaneously, the system can overcome the challenges of detecting objects in dense smoke. The four detailed methods proposed are as follows: First, a 3D ultrasonic sensor system that detects the 3D position of an object at a short distance and i
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Schlemmer, Matthias J., Georg Biegelbauer, and Markus Vincze. "Rethinking Robot Vision – Combining Shape and Appearance." International Journal of Advanced Robotic Systems 4, no. 3 (2007): 29. http://dx.doi.org/10.5772/5691.

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Equipping autonomous robots with vision sensors provides a multitude of advantages by simultaneously bringing up difficulties with regard to different illumination conditions. Furthermore, especially with service robots, the objects to be handled must somehow be learned for a later manipulation. In this paper we summarise work on combining two different vision sensors, namely a laser range scanner and a monocular colour camera, for shape-capturing, detecting and tracking of objects in cluttered scenes without the need of intermediate user interaction. The use of different sensor types provides
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Kasinath, S., S. K. Stephan, Edward Lisha, K.G. Parthive, and R. Remya. "Enhanced Blind Navigation using YOLO and Sensor Fusion." Recent Innovations in Wireless Network Security 7, no. 3 (2025): 1–10. https://doi.org/10.5281/zenodo.15516516.

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<em>Blind navigation remains a significant challenge for visually impaired individuals, particularly in complex and dynamic environments such as crowded streets, public transport, and indoor spaces. Traditional mobility aids like canes and guide dogs offer assistance but have limitations in detecting fast-moving obstacles or recognizing objects beyond immediate reach. With advancements in artificial intelligence (AI) and sensor technologies, there is an opportunity to develop smarter, real-time navigation solutions that enhance mobility and independence for visually impaired individuals.</em>
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Wahyu Rizki Ananda, Abdul Jabbar Lubis, and Ummul Khair. "Implementation of Motion Sensors and Buzzers on Robots to Detect Object Movement." Journal of Artificial Intelligence and Engineering Applications (JAIEA) 4, no. 2 (2025): 1354–61. https://doi.org/10.59934/jaiea.v4i2.907.

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Technological advances in this modern era have brought many significant changes in various fields, including security and surveillance. One innovation that stands out is the use of robots to detect object movement. This research aims to implement motion sensors and buzzers on robots to detect the movement of objects around them. This system uses a Passive Infrared (PIR) sensor to detect changes in infrared radiation produced by object movement, and a buzzer as an auditory warning device when movement is detected. In addition, the robot is designed to operate automatically by identifying moveme
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Dissertations / Theses on the topic "Object Detecting Sensors"

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Fernandes, Rui Miguel Félix. "Object signature in radio frequency." Master's thesis, Universidade de Aveiro, 2014. http://hdl.handle.net/10773/13708.

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Mestrado em Engenharia Eletrónica e Telecomunicações<br>The RF signature can be consider as a fingerprint of an object when submitted to electromagnetic radiation. Based on this concept, the initial goal of this work was to elaborate a comparative analysis of the Radio Frequency signature of different materials. Through the design of a prototype based on an adapted Wi-Fi network was developed an innovative system capable of distinguishing materials with the analysis of their interference in the propagated channel. In order to refine this distinction was utilized a signal processing tool, the
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Sikdar, Ankita. "Depth based Sensor Fusion in Object Detection and Tracking." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1515075130647622.

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Gudipudi, Venkata Naga Manikanta Aditya. "Detection and velocity of a fast moving object." Thesis, Blekinge Tekniska Högskola, Institutionen för tillämpad signalbehandling, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-14400.

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Over a past few years, technology is constructing the way humans live. With the rapid growth towards Internet of Things (IOT) and other connected services, companies are investigating the ways to enhance current living conditions. There are several devices that are launched in the market to help people to increase flexibility and most of all, to see beyond what is possible. It is helping us reinforce ourselves in our day to day activities. Even in sports, thanks to the latest technological developments, most people’s lives have been enhanced and simplified. Advances in technology has a huge im
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Tun, Min Han. "Virtual image sensors to track human activity in a smart house." Thesis, Curtin University, 2007. http://hdl.handle.net/20.500.11937/904.

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With the advancement of computer technology, demand for more accurate and intelligent monitoring systems has also risen. The use of computer vision and video analysis range from industrial inspection to surveillance. Object detection and segmentation are the first and fundamental task in the analysis of dynamic scenes. Traditionally, this detection and segmentation are typically done through temporal differencing or statistical modelling methods. One of the most widely used background modeling and segmentation algorithms is the Mixture of Gaussians method developed by Stauffer and Grimson (199
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Venkataraayan, Kavitha. "Multi-wavelength, multi-beam, photonic based sensor for object discrimination and positioning." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2012. https://ro.ecu.edu.au/theses/488.

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Over the last decade, substantial research efforts have been dedicated towards the development of advanced laser scanning systems for discrimination in perimeter security, defence, agriculture, transportation, surveying and geosciences. Military forces, in particular, have already started employing laser scanning technologies for projectile guidance, surveillance, satellite and missile tracking; and target discrimination and recognition. However, laser scanning is relatively a new security technology. It has previously been utilized for a wide variety of civil and military applications. Terres
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Javed, Omar. "SCENE MONITORING WITH A FOREST OF COOPERATIVE SENSORS." Doctoral diss., University of Central Florida, 2005. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/3448.

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In this dissertation, we present vision based scene interpretation methods for monitoring of people and vehicles, in real-time, within a busy environment using a forest of co-operative electro-optical (EO) sensors. We have developed novel video understanding algorithms with learning capability, to detect and categorize people and vehicles, track them with in a camera and hand-off this information across multiple networked cameras for multi-camera tracking. The ability to learn prevents the need for extensive manual intervention, site models and camera calibration, and provides adaptability to
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Jiang, Lixing [Verfasser]. "Object Recognition and Saliency Detection for Indoor Robots using RGB-D Sensors / Lixing Jiang." München : Verlag Dr. Hut, 2016. http://d-nb.info/1106593723/34.

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Giovanelli, Debora. "Electrochemical detection of gases." Thesis, University of Oxford, 2004. http://ora.ox.ac.uk/objects/uuid:fd447153-b6dd-4be1-aae5-4ece5dc36856.

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This thesis discusses diverse electrochemical strategies for the determination of the concentration of the gases hydrogen sulfide, ammonia and halothane. The chemical tagging of sulfide by a variety of structurally diverse substituted benzoquinone species was studied over a wide range of pH (2<pH<10). Each derivative was found to respond to increasing concentration of sulfide (typically over a range 10-200 μM). The electrochemically initiated reaction of N,N-diethyl-pphenylenediamine (DEPD) with sulfide in N,N-dimethylformamide (DMF) was next examined with quantitative detection of sulfide (li
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Lima, João Paulo Silva do Monte. "Object detection and pose estimation from rectification of natural features using consumer RGB-D sensors." Universidade Federal de Pernambuco, 2014. https://repositorio.ufpe.br/handle/123456789/12143.

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Submitted by Nayara Passos (nayara.passos@ufpe.br) on 2015-03-12T13:53:20Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) TESE João Paulo Silva do Monte Lima.pdf: 5689244 bytes, checksum: e6e2c3f1da85d18b6bb7049e458f50e7 (MD5)<br>Made available in DSpace on 2015-03-12T13:53:20Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) TESE João Paulo Silva do Monte Lima.pdf: 5689244 bytes, checksum: e6e2c3f1da85d18b6bb7049e458f50e7 (MD5) Previous issue date: 2014<br>CAPES , CNPq<br>Sistemas de R
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Tun, Min Han. "Virtual image sensors to track human activity in a smart house." Curtin University of Technology, School of Computing, 2007. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=17557.

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With the advancement of computer technology, demand for more accurate and intelligent monitoring systems has also risen. The use of computer vision and video analysis range from industrial inspection to surveillance. Object detection and segmentation are the first and fundamental task in the analysis of dynamic scenes. Traditionally, this detection and segmentation are typically done through temporal differencing or statistical modelling methods. One of the most widely used background modeling and segmentation algorithms is the Mixture of Gaussians method developed by Stauffer and Grimson (199
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Books on the topic "Object Detecting Sensors"

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Yuan-Liang, Tang, Devadiga Sadashiva, and United States. National Aeronautics and Space Administration., eds. A model-based approach for detection of objects in low resolution passive millimeter wave images: An interim report for NASA grant NAG-1-1371, "analysis of image sequences from sensors for restricted visibility operations", for the period January 24, 1992 to January 23, 1993. Dept. of Electrical and COmputer Engineering, Pennsylvania State University, 1993.

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Yuan-Liang, Tang, Devadiga Sadashiva, and United States. National Aeronautics and Space Administration., eds. A model-based approach for detection of objects in low resolution passive millimeter wave images: An interim report for NASA grant NAG-1-1371, "analysis of image sequences from sensors for restricted visibility operations", for the period January 24, 1992 to January 23, 1993. Dept. of Electrical and COmputer Engineering, Pennsylvania State University, 1993.

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United States. National Aeronautics and Space Administration., ed. A model-based approach for detection of runways and other objects in image sequences acquired using an on-board camera: Final technical report for NASA grant NAG-1-1371, "analysis of image sequences from sensors for restricted visibility operations", period of the grant January 24, 1992 to May 31, 1994. National Aeronautics and Space Administration, 1994.

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United States. National Aeronautics and Space Administration., ed. A model-based approach for detection of runways and other objects in image sequences acquired using an on-board camera: Final technical report for NASA grant NAG-1-1371, "analysis of image sequences from sensors for restricted visibility operations", period of the grant January 24, 1992 to May 31, 1994. National Aeronautics and Space Administration, 1994.

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United States. National Aeronautics and Space Administration., ed. A model-based approach for detection of runways and other objects in image sequences acquired using an on-board camera: Final technical report for NASA grant NAG-1-1371, "analysis of image sequences from sensors for restricted visibility operations", period of the grant January 24, 1992 to May 31, 1994. National Aeronautics and Space Administration, 1994.

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Kapilevich, Boris Y., Stuart W. Harmer, and Nicholas J. Bowring. Non-Imaging Microwave and Millimetre-Wave Sensors for Concealed Object Detection. Taylor & Francis Group, 2017.

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Kapilevich, Boris Y., Stuart W. Harmer, and Nicholas J. Bowring. Non-Imaging Microwave and Millimetre-Wave Sensors for Concealed Object Detection. Taylor & Francis Group, 2017.

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Harmer, Stuart William, Boris Kapilevich, and Nicholas Bowring. Non-Imaging Microwave and Millimetre-Wave Sensors for Concealed Object Detection. Taylor & Francis Group, 2015.

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Kapilevich, Boris Y., Stuart W. Harmer, and Nicholas J. Bowring. Non-Imaging Microwave and Millimetre-Wave Sensors for Concealed Object Detection. Taylor & Francis Group, 2017.

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Kapilevich, Boris Y., Stuart W. Harmer, and Nicholas J. Bowring. Non-Imaging Microwave and Millimetre-Wave Sensors for Concealed Object Detection. Taylor & Francis Group, 2017.

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Book chapters on the topic "Object Detecting Sensors"

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Kang, Byungmun, and DaeEun Kim. "Detecting a Sphere Object with an Array of Magnetic Sensors." In From Animals to Animats 15. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-97628-0_11.

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Lee, Seungsoo, Seongwoo Son, Pa Pa Win Aung, Minsoo Park, and Seunghee Park. "Deep Learning Based Pose Estimation of Scaffold Fall Accident Safety Monitoring." In CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality. Firenze University Press, 2023. http://dx.doi.org/10.36253/979-12-215-0289-3.63.

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According to the Ministry of Manpower, falling and slipping accidents are one of the most common accidents in addition, falls from heights (FFH), including accidents during scaffolding work, are still a major cause of death in the construction industry. Regular safety checks are currently being carried out on construction sites, but scaffold-related accidents continue to occur. Sensing technology is being attempted in many industrial sites for safety monitoring, but there are still limitations in terms of the cost of sensors and object detection, which are limited to certain risks. Therefore,
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Lee, Seungsoo, Seongwoo Son, Pa Pa Win Aung, Minsoo Park, and Seunghee Park. "Deep Learning Based Pose Estimation of Scaffold Fall Accident Safety Monitoring." In CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality. Firenze University Press, 2023. http://dx.doi.org/10.36253/10.36253/979-12-215-0289-3.63.

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According to the Ministry of Manpower, falling and slipping accidents are one of the most common accidents in addition, falls from heights (FFH), including accidents during scaffolding work, are still a major cause of death in the construction industry. Regular safety checks are currently being carried out on construction sites, but scaffold-related accidents continue to occur. Sensing technology is being attempted in many industrial sites for safety monitoring, but there are still limitations in terms of the cost of sensors and object detection, which are limited to certain risks. Therefore,
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Gamerdinger, Jörg, Georg Volk, Sven Teufel, et al. "Robust Local and Cooperative Perception Under Varying Environmental Conditions." In Cooperatively Interacting Vehicles. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-60494-2_5.

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AbstractRobust perception of the environment under a variety of ambient conditions is crucial for autonomous driving. Convolutional Neural Networks (CNNs) achieve high accuracy for vision-based object detection, but are strongly affected by adverse weather conditions such as rain, snow, and fog, as well as soiled sensors. We propose physically correct simulations of these conditions for vision-based systems, since publicly available data sets lack scenarios with different environmental conditions. In addition, we provide a data set of real images containing adverse weather for evaluation. By t
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Zhang, Xinyu, Jun Li, Zhiwei Li, et al. "Multi-Sensor Object Detection." In Multi-sensor Fusion for Autonomous Driving. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-3280-1_4.

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Gölz, Jacqueline, and Christian Hatzfeld. "Sensor Design." In Springer Series on Touch and Haptic Systems. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-04536-3_10.

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AbstractMultiple sensors are applied in haptic devices designs. Even if they are not closed-loop controlled in a narrow sense of force or torque generation, they are used to detect movement ranges and limits or the detection of the presence of a user and its type of interaction with an object or human-machine-interface (HMI). Almost any type of technical sensor had been applied in the context of haptic devices. The emerging market of gesture based user interaction and integration of haptics due to ergonomic reasons extends the range of sensors potentially relevant for haptic devices. However,
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Yoshitake, Hiroshi, Jinyu Gu, and Motoki Shino. "Occluded Area Detection Based on Sensor Fusion and Panoptic Segmentation." In Lecture Notes in Mechanical Engineering. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-70392-8_66.

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AbstractDetecting occluded areas in a driving environment is crucial to preventing traffic accidents against hidden road agents coming out from such occluded areas. Our previous work proposed a novel detection method that can offer geometric information of the detected areas by utilizing camera and LiDAR sensor fusion. However, it had difficulty identifying individual areas formed by different objects without information about distinct objects. Thus, the objective of this study was to improve our previous methodology, and panoptic segmentation, which can distinguish between individual objects
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Frintrop, Simone. "6 Sensor Fusion." In VOCUS: A Visual Attention System for Object Detection and Goal-Directed Search. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11682110_6.

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Dong, Lanfang, Jiakui Yu, Jianfu Wang, and Weinan Gao. "Research of a Framework for Flow Objects Detection and Tracking in Video." In Wearable Sensors and Robots. Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-2404-7_36.

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Cao, Xuyang, Yongchang Hu, Guoyang Xu, Shuai Song, and Xiaochun Tie. "A Machine-Vision-Based Hub Location Detection Technique for Installing Wind Turbines." In Lecture Notes in Mechanical Engineering. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-1876-4_30.

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AbstractA position detection approach based on machine vision is developed to address the issue that the traditional wind turbine hub lifting procedure relies on the location of engineers and cannot provide quick feedback on the position information. A camera and a range sensor are mounted on the suspended object to enable real-time detection of the fan hub’s posture state in relation to the engine room. A monocular camera positioning technique based on circular features is created for this detection method. The relative pose coordinates of the hub are computed using the position data given by
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Conference papers on the topic "Object Detecting Sensors"

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Meiresone, Pieter, David Van Hamme, and Wilfried Philips. "Event Intensity Decay with Event Cameras for Efficient Object Detection." In 2024 IEEE SENSORS. IEEE, 2024. https://doi.org/10.1109/sensors60989.2024.10784654.

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Shen, Chongqiang, Xiangyun Ren, Dongfang Yang, Yang Chen, Lihong Qiu, and Ke Wang. "Uncertainty-Based Semi-Supervised Object Detection in Autonomous Driving Environment." In 2024 IEEE SENSORS. IEEE, 2024. https://doi.org/10.1109/sensors60989.2024.10784752.

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Lin, Junan, Stefano Maranó, Bruno Arsenali, et al. "Enhancing Port Automation: A Novel Object Detection Pipeline for Container Ship Bays." In 2024 IEEE SENSORS. IEEE, 2024. https://doi.org/10.1109/sensors60989.2024.10784915.

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Kon, Seitaro, and Ryosaku Kaji. "Detection of Hidden non-Metallic Objects Using Electromagnetic Field." In 2024 IEEE SENSORS. IEEE, 2024. https://doi.org/10.1109/sensors60989.2024.10784473.

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Kuroda, Keiichiro, Yudai Morikaku, Yu Osuka, Ryoya Iegaki, Kota Yoshida, and Shunsuke Okura. "Lightweight Object Detection Model for a CMOS Image Sensor with Binary Feature Extraction." In 2024 IEEE SENSORS. IEEE, 2024. https://doi.org/10.1109/sensors60989.2024.10784814.

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Maktedar, Asrarulhaq, and Mayurika Chatterjee. "Best Practices in Sensor Selection for Object Detection in Autonomous Driving: A Practitioner’s Perspective." In 11th SAEINDIA International Mobility Conference (SIIMC 2024). SAE International, 2024. https://doi.org/10.4271/2024-28-0218.

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&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;Object detection (OD) is one of the most important aspects in Autonomous Driving (AD) application. This depends on the strategic sensor’s selection and placement of sensors around the vehicle. The sensors should be selected based on various constraints such as range, use-case, and cost limitation. This paper introduces a systematic approach for identifying the optimal practices for selecting sensors in AD object detection, offering guidance for those looking to expand their expertise in this field and select the most sui
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Cardwell, D. N., K. S. Chana, and M. T. Gilboy. "The Development and Testing of a Gas Turbine Engine Foreign Object Damage (FOD) Detection System." In ASME Turbo Expo 2010: Power for Land, Sea, and Air. ASMEDC, 2010. http://dx.doi.org/10.1115/gt2010-23478.

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This paper details the development of a prototype in-flight foreign object damage (FOD) detection system through various stages, resulting in a system capable of detecting objects as small as one gram (1g) mass. The system comprises an eddy current sensor based tip timing system and acoustic emissions vibration sensors controlled through a digital signal processor (DSP). QinetiQ have developed light weight, contamination-immune eddy current tip timing sensors for use in engine health management. Engine tests confirmed these sensors’ potential for detecting FOD events. FOD detection algorithms
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Cotton, Darryl, Andy Cranny, Neil White, Steve Beeby, and Paul Chappell. "Design and Development of Integrated Thick-Film Sensors for Prosthetic Hands." In ASME 7th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2004. http://dx.doi.org/10.1115/esda2004-58027.

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The majority of prosthetic hands lack an intelligent feedback control system requiring the user to rely on either visual feedback to detect whether an object is slipping out of the hand or if an unnecessarily large force is being applied. Screen printed thick film piezoresistive resistors and piezoelectric dynamic sensors offer a cheap and compact solution for detecting grip force and slip of an object from a prosthesis. This paper investigates the surface strain produced on two different fingertip designs with different attachment and loading methods in an attempt to optimise sensor position
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Kim, Sung Joon, and Ja Choon Koo. "A New Highly Sensitive Dielectric Slip Detection Sensor for a Robotic Operation." In ASME 2017 Conference on Information Storage and Processing Systems collocated with the ASME 2017 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/isps2017-5403.

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For dexterous grasping and manipulation, tactile sensors recognizing contact object are essential. Electronic skin (E-skin) with tactile sensors plays a role as both receiving information for grasping and protecting robot frame. This paper presents a polymer tactile sensor covering large area to fulfill role of E-skin. The sensor has a thin air gap between polymer layers and it is deformed reacting slip input. When slip is occurred, there is relative displacement between surrounding layer and it incurs change of electrode separation. NBR is used to sensor substrate because of its tough and fle
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Kim, Sung Joon, Jae Young Choi, Hyung Pil Moon, Hyouk Ryeol Choi, and Ja Choon Koo. "Detection of Slippage Using Flexible Tactile Sensor for a Robot Fingertip." In ASME 2016 Conference on Information Storage and Processing Systems. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/isps2016-9567.

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Tactile sensor for detecting slip is essential to grasp an object safely in a robot hand with a complicated structure and various functions. In this paper, sensors with three patterns in different forms are designed to sense slip moment through a resistance change. The slip sensors developed in this paper have flexible and stretchable characteristics to be used on the robot hand surface. For realizing these characteristics, acrylonitrile-butadiene rubber (NBR) is used as a substrate of the sensor. Graphene material is employed bacause of suitable for flexible substrate as an electrode. An impr
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Reports on the topic "Object Detecting Sensors"

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Clausen, Jay, Vuong Truong, Sophia Bragdon, et al. Buried-object-detection improvements incorporating environmental phenomenology into signature physics. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/45625.

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The ability to detect buried objects is critical for the Army. Therefore, this report summarizes the fourth year of an ongoing study to assess environ-mental phenomenological conditions affecting probability of detection and false alarm rates for buried-object detection using thermal infrared sensors. This study used several different approaches to identify the predominant environmental variables affecting object detection: (1) multilevel statistical modeling, (2) direct image analysis, (3) physics-based thermal modeling, and (4) application of machine learning (ML) techniques. In addition, th
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Clausen, Jay, Susan Frankenstein, Jason Dorvee, et al. Spatial and temporal variance of soil and meteorological properties affecting sensor performance—Phase 2. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/41780.

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An approach to increasing sensor performance and detection reliability for buried objects is to better understand which physical processes are dominant under certain environmental conditions. The present effort (Phase 2) builds on our previously published prior effort (Phase 1), which examined methods of determining the probability of detection and false alarm rates using thermal infrared for buried-object detection. The study utilized a 3.05 × 3.05 m test plot in Hanover, New Hampshire. Unlike Phase 1, the current effort involved removing the soil from the test plot area, homogenizing the mat
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Yan, Yujie, and Jerome F. Hajjar. Automated Damage Assessment and Structural Modeling of Bridges with Visual Sensing Technology. Northeastern University, 2021. http://dx.doi.org/10.17760/d20410114.

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Recent advances in visual sensing technology have gained much attention in the field of bridge inspection and management. Coupled with advanced robotic systems, state-of-the-art visual sensors can be used to obtain accurate documentation of bridges without the need for any special equipment or traffic closure. The captured visual sensor data can be post-processed to gather meaningful information for the bridge structures and hence to support bridge inspection and management. However, state-of-the-practice data postprocessing approaches require substantial manual operations, which can be time-c
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Clausen, Jay, Rosa Affleck, Christopher Felt, et al. Modernizing environmental signature physics for target detection. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/41240.

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The objective of this study was to determine the effect of environmental phenomonology on the ability to detect buried objects and to provide a predictive capability of when targets are best detectable with IR sensors. Jay Clausen presented this material at the ERDC RD20 Conference.
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Porcel Magnusson, Cristina. Unsettled Topics Concerning Coating Detection by LiDAR in Autonomous Vehicles. SAE International, 2021. http://dx.doi.org/10.4271/epr2021002.

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Autonomous vehicles (AVs) utilize multiple devices, like high-resolution cameras and radar sensors, to interpret the driving environment and achieve full autonomy. One of these instruments—the light detection and ranging (LiDAR) sensor—utilizes pulsed infrared (IR) light, typically at wavelengths of 905 nm or 1,550 nm, to calculate object distance and position. Exterior automotive paint covers an area larger than any other exterior material. Therefore, understanding how LiDAR wavelengths interact with vehicle coatings is extremely important for the safety of future automated driving technologi
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McVay, John. Satellite Enveloped with STITCHED Engineering Sensors for Detection of Approaching Objects. Office of Scientific and Technical Information (OSTI), 2022. http://dx.doi.org/10.2172/1893245.

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Musty, Michael, Vuong Truong, Jay Clausen, et al. Thermal infra-red comparison study of buried objects between humid and desert test beds. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/45064.

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This study pertains to the thermal variations caused by buried objects and their ramifications on soil phenomenology. A multitude of environmental conditions were investigated to observe the effect on thermal infrared sensor performance and detection capabilities. Correlations between these external variables and sensor contrast metrics enable determinable key factors responsible for sensor degradation. This document consists of two parts. The first part is a summary of data collected by the U.S. Army Corps of Engineers, Engineer and Research and Development Center Cold Regions Research and En
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Down, Murray. PR686-203903-R02 Ongoing InSAR Geohazard Monitoring of Pipeline Right-of Ways in the Appalachian Mountains. Pipeline Research Council International, Inc. (PRCI), 2021. http://dx.doi.org/10.55274/r0012178.

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Ground displacement along pipeline corridors has the potential to compromise pipeline integrity. The Appalachian Mountain region is almost entirely classed as high landslide susceptibility by the United States Geological Survey (USGS) and crossed by numerous transmission pipelines and gathering lines. In phase I of this research project, 3vGeomatics successfully demonstrated a proof of concept on the effectiveness, reliability, and precision of using L-band ( ) SAR satellites for InSAR displacement monitoring of vegetated areas. The second phase of this project improved operational monitoring
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Tao, Yang, Victor Alchanatis, and Yud-Ren Chen. X-ray and stereo imaging method for sensitive detection of bone fragments and hazardous materials in de-boned poultry fillets. United States Department of Agriculture, 2006. http://dx.doi.org/10.32747/2006.7695872.bard.

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As Americans become increasingly health conscious, they have increased their consumptionof boneless white and skinless poultry meat. To the poultry industry, accurate detection of bonefragments and other hazards in de-boned poultry meat is important to ensure food quality andsafety for consumers. X-ray imaging is widely used for internal material inspection. However,traditional x-ray technology has limited success with high false-detection errors mainly becauseof its inability to consistently recognize bone fragments in meat of uneven thickness. Today’srapid grow-out practices yield chicken bo
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Workman, Austin, and Jay Clausen. Meteorological property and temporal variable effect on spatial semivariance of infrared thermography of soil surfaces for detection of foreign objects. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/41024.

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The environmental phenomenological properties responsible for the thermal variability evident in the use of thermal infrared (IR) sensor systems is not well understood. The research objective of this work is to understand the environmental and climatological properties contributing to the temporal and spatial thermal variance of soils. We recorded thermal images of surface temperature of soil as well as several meteorological properties such as weather condition and solar irradiance of loamy soil located at the Cold Regions Research and Engineering Lab (CRREL) facility. We assessed sensor perf
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