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Journal articles on the topic 'Robotic system identification'
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Ghiță, Alexandra Ștefania, and Adina Magda Florea. "Real-Time People Re-Identification and Tracking for Autonomous Platforms Using a Trajectory Prediction-Based Approach." Sensors 22, no. 15 (August 5, 2022): 5856. http://dx.doi.org/10.3390/s22155856.
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Currently, the importance of autonomous operating devices is rising with the increasing number of applications that run on robotic platforms or self-driving cars. The context of social robotics assumes that robotic platforms operate autonomously in environments where people perform their daily activities. The ability to re-identify the same people through a sequence of images is a critical component for meaningful human-robot interactions. Considering the quick reactions required by a self-driving car for safety considerations, accurate real-time tracking and people trajectory prediction are mandatory. In this paper, we introduce a real-time people re-identification system based on a trajectory prediction method. We tackled the problem of trajectory prediction by introducing a system that combines semantic information from the environment with social influence from the other participants in the scene in order to predict the motion of each individual. We evaluated the system considering two possible case studies, social robotics and autonomous driving. In the context of social robotics, we integrated the proposed re-identification system as a module into the AMIRO framework that is designed for social robotic applications and assistive care scenarios. We performed multiple experiments in order to evaluate the performance of our proposed method, considering both the trajectory prediction component and the person re-identification system. We assessed the behaviour of our method on existing datasets and on real-time acquired data to obtain a quantitative evaluation of the system and a qualitative analysis. We report an improvement of over 5% for the MOTA metric when comparing our re-identification system with the existing module, on both evaluation scenarios, social robotics and autonomous driving.
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Swamy, Puchala Jaswanth Phaneendra, B. YeswanthKumar Reddy, and K. Chandrasekhar. "Intelligent Surveillance Using Robot Eye and Sensor System." Applied Mechanics and Materials 917 (October 13, 2023): 27–38. http://dx.doi.org/10.4028/p-4yneed.
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Majority of the advancements, which have been made in the field of robotics are employed in household applications. Surveillance systems are used in guarding and security applications of household and workplaces. This paper presents an advanced surveillance system which integrates sensor system, robot technology and intelligent programming. Robotic surveillance system can be used to replace human guards in dangerous surveillance conditions. Several robots have been developed to assist in these operations. But the full scale employment of robots in crucial fields such as surveillance, security in defence industries and military bases is very limited. The system's overall structure is described, along with descriptions of each component. The robotic system consists of robot eyes, which are capable of sensing an object through IR sensor capability. This robotic system helps in the identification of human presence and alerting respective owners. These operations, performed by the robotic system are achieved using sensors, several number of servo motors, Arduino microcontroller. These components are placed in their respective locations, within a body which is fabricated using the 3D printing technology. The sensors in the robotic system capture the movements of objects. The robotic eyes are fitted with cameras which capture the movements. The robotic system is programmed in such a way that the robotic eyes, move in the direction of object which has been sensed by the sensors and focus on it. If there are multiple moving objects, then one robotic eye focuses on one object, while the other robotic eye focuses on another object. The captured surveillance footage can be viewed through a monitor connected to the robotic system.
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Prado da Fonseca, Vinicius. "Tactile Sensor Analysis during Early Stages of Manipulation for Single Grasp Identification of Daily Objects." Engineering Proceedings 6, no. 1 (May 17, 2021): 56. http://dx.doi.org/10.3390/i3s2021dresden-10091.
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Dexterous robotic manipulation in unstructured environments is still challenging, despite the increasing number of robots entering human settings each day. Even though robotic manipulation provides complete solutions in factories and industries, it still lacks essential techniques, displaying clumsy or limited operation in unstructured environments. Daily objects typically aim at the human hand, and the human somatosensory system is responsible for solving all the complex calculations required for dexterous manipulations in unstructured settings. Borrowing concepts of the human visuotactile system can improve dexterous manipulation and increase robotics usage in unstructured environments. In humans, required finger and wrist joint adjustments occur after fast identification of the object in the initial stages of manipulation. Fast object identification during those phases may increase robotic dexterous manipulation performance. The present paper explores human-inspired concepts such as haptic glance to develop robotic single-grasp object identification. This concept can assist early phases of robotic manipulation, helping automated decision-making, such as type of grasp and joint position, during manipulation tasks. The main stages developed here are detecting sensor activation and sample collection using signal-to-noise and z-score filtering on tactile data. This procedure automates touch detection and reduces the sensor space for classification. Experiments on a daily objects dataset presented compelling results that will assist in the later stages of the early phases of robotic grasping.
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Angel, L., J. Viola, and C. Hernández. "Parametric uncertain identification of a robotic system." IOP Conference Series: Materials Science and Engineering 138 (July 2016): 012008. http://dx.doi.org/10.1088/1757-899x/138/1/012008.
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Shafie, Amir Akramin, Azhar Bin Mohd Ibrahim, and Muhammad Mahbubur Rashid. "Smart Objects Identification System for Robotic Surveillance." International Journal of Automation and Computing 11, no. 1 (February 2014): 59–71. http://dx.doi.org/10.1007/s11633-014-0766-9.
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Ojha, Varsha. "Robotics In Gynecology- A Review." Obstetrics Gynecology and Reproductive Sciences 8, no. 5 (July 26, 2024): 01–07. http://dx.doi.org/10.31579/2578-8965/224.
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This review article focuses on the development of robotics-based operations in the medical field especially in gynecology. The goal of the surgical robot is to improve surgical skills and compensate for human limitations. The robot's performance in performing duties correctly and consistently has been the key to its success. Tubal anastomosis was the first gynecologic surgery performed with Robotic assistance in 2000 followed by first Robotic Hysterectomy in 2002. In 2003 Da Vinci surgical system was developed which was FDA approved for gynecological surgery in 2005. It has gained popularity fast and is already playing a big part in many of the places where it is available. It consists of a high-resolution three-dimensional (3D) vision system adjacent to the patient on a cart with robotic branches. It provides unique technical advancement, with tremor filtration, improved ergonomics and lower muscular load as compared to both laparoscopic and open surgeries. Autonomous camera and energy instrument control, wrist articulation with 7 degree freedom, telestration and dual- console capabilities, overcoming the limitations of conventional laparoscopy, such as counterintuitive hand movements, 2 dimensional visualization, limited degree of motion and tremor amplification. Compared to laparoscopy, robotic assistance has a lower conversion rate to open procedures. Endo wrist movement of an automated machine during myomectomy surgery can perform proper and better suturing than traditional laparoscopy. The automated program is a noticeable improvement over laparoscopic surgery and, if price issues are resolved, can gain popularity among gynecological surgeons around the globe. Not unique to robotic system, the integration of indigo cyanine green fluorescence with the Da Vinci robotic system allows identification of lesions, and assessment of perfusion of bowel and ureter during deep infiltrating endometriosis resection.
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Karras, George C., Panos Marantos, Charalampos P. Bechlioulis, and Kostas J. Kyriakopoulos. "Unsupervised Online System Identification for Underwater Robotic Vehicles." IEEE Journal of Oceanic Engineering 44, no. 3 (July 2019): 642–63. http://dx.doi.org/10.1109/joe.2018.2827678.
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Condés, Ignacio, Jesús Fernández-Conde, Eduardo Perdices, and José M. Cañas. "Robust Person Identification and Following in a Mobile Robot Based on Deep Learning and Optical Tracking." Electronics 12, no. 21 (October 27, 2023): 4424. http://dx.doi.org/10.3390/electronics12214424.
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There is an exciting synergy between deep learning and robotics, combining the perception skills a deep learning system can achieve with the wide variety of physical responses a robot can perform. This article describes an embedded system integrated into a mobile robot capable of identifying and following a specific person reliably based on a convolutional neural network pipeline. In addition, the design incorporates an optical tracking system for supporting the inferences of the neural networks, allowing the determination of the position of a person using an RGB depth camera. The system runs on an NVIDIA Jetson TX2 board, an embedded System-on-Module capable of performing computationally demanding tasks onboard and handling the complexity needed to run a solid tracking and following algorithm. A robotic mobile base with the Jetson TX2 board attached receives velocity orders to move the system toward the target. The proposed approach has been validated on a mobile robotic platform that successfully follows a determined person, relying on the robustness of the combination of deep learning with optical tracking for working efficiently in a real environment.
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Rupali S. Kokate, Saniya Ansari, S. M. Khairnar, Ravindra R. Patil,. "AN ASSESSMENT - WATER QUALITY MONITORING PRACTICES AND SEWER ROBOTIC SYSTEMS." INFORMATION TECHNOLOGY IN INDUSTRY 9, no. 1 (February 28, 2021): 140–48. http://dx.doi.org/10.17762/itii.v9i1.113.
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Water pollution has become a global issue and creating a severe problems due to contamination of various water sources such as agricultural waste, industrial waste, and sewage waste etc. So, the available sensory systems, nodes, and techniques plays a crucial role in identification of harmful pollutants in distinct water resources. The water pollutants monitoring techniques with prospered tools and sensors have been unfolded to find gap for future research maneuver. The need of real-time newer sensory system has been put forwarded for identification of mostly occurring harmful pollutants such as BOD, COD, TSS, and Hydrogen sulfide in examination of water quality.
In this modern advancement, robotic systems have taken an intrinsic stand in diverse fields of humankind. An underground infrastructure is a base of modern society. In this paper, the existing methodologies and developed sewer robotic systems have been discussed and concluded on their applications, limitations and impact on realistic scenarios. Also, the cardinal point is revealed that previous art work focused only on sewer defect identification but not standardized work on sewer blockages detection and removal. So, the sewer robotic system with features of cost effectiveness and standardized accuracy matrix should be developed to resolve sewer blockage issues and followed by human scavenging. The survey outcomes extend a province of sewer robotics to resolve blockages issues of buried sewers of distinct diameters in real-time with substantial methodology.
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García-Luna, F., and A. Morales-Díaz. "Towards an artificial vision-robotic system for tomato identification." IFAC-PapersOnLine 49, no. 16 (2016): 365–70. http://dx.doi.org/10.1016/j.ifacol.2016.10.067.
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Foo, Gwendolyn, Sami Kara, and Maurice Pagnucco. "An Ontology-Based Method for Semi-Automatic Disassembly of LCD Monitors and Unexpected Product Types." International Journal of Automation Technology 15, no. 2 (March 5, 2021): 168–81. http://dx.doi.org/10.20965/ijat.2021.p0168.
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Disassembly is a vital step in any treatment stream of waste electrical and electronic equipment (WEEE), preventing hazardous and toxic chemicals and materials from damaging the ecosystem. However, the large variations and uncertainties in WEEE is a major limitation to the implementation of automation and robotics in this field. Therefore, the advancement of robotic and automation intelligence to be flexible in handling a variety of situations in WEEE disassembly is sought after. This paper presents an ontology-based cognitive method for generating actions for the disassembly of WEEE, with a focus on LCD monitors, handling uncertainties throughout the disassembly process. The system utilizes reasoning about relationships between a typical LCD monitor product, component features, common fastener types, and actions that the system is capable of, to determine 4 key stages of robotic disassembly: component identification, fastener identification, disassembly action generation, and identification of disassembly extent. Further uncertainties in the form of possible failure of action execution is reasoned about to provide new actions, and any unusual scenarios that result in incorrect reasoning outputs are rectified with user-demonstration as a last resort. The proposed method is trialed for the disassembly of LCD monitors and a product unknown to the system, in the form of a DVD-ROM drive.
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AGUILERA, R. CARREÑO, F. AGUILAR ACEVEDO, M. PATIÑO ORTIZ, and J. PATIÑO ORTIZ. "ROBOTIC ARM WITH BIoT MACHINE LEARNING SYSTEM." Fractals 28, no. 04 (May 12, 2020): 2050088. http://dx.doi.org/10.1142/s0218348x20500887.
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In this work, we present a robotic arm assisted by a visual system to decide whether an object with different colors, parallel flat surfaces and other types of surfaces would be subject to be manipulated without a drop risk. This robotic arm is assisted with sensors such as temperature, humidity, artificial vision, etc. and monitored with a Blockchain Internet of Things (BIoT) expert system assistance, which is shared and accessed by the internet by the users. A prototype for industrial purpose is launched to start providing data for training the expert system, achieving in this way an expert system with machine learning. The variations derived from the identification of the reference points and the characteristics of the robotic arm are a limiting factor of the system, however, it was possible to correctly locate the robotic arm in the workspace to take the object and manipulate it using machine learning based on a BIoT expert system.
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Jiménez Builes, Jovani Alberto, Demetrio Arturo Ovalle Carranza, and John William Branch Bedoya. "Multiple robot systems’ communication using MAD-Smart methodology." Ingeniería e Investigación 28, no. 2 (May 1, 2008): 59–65. http://dx.doi.org/10.15446/ing.investig.v28n2.14893.
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This paper was aimed at exhibiting the real need for having good communication within multiple robots systems using MAD-Smart methodology. Such methodology consists of conceptualising, analysing and designing multiple robot teams by defining a set of activities. MAD-Smart assists developers in further understanding not only the problem to be solved but the final characteristics which a particular system must accomplish and the role played by each agent in resolving problems. This methodology has already been validated by implementing the SMART (robotic multi agent system) project, educational robotics: intelligent machines in education and sensory and perception models in robotic agents for material identification. MAD-Smart has been shown to be more relevant in handling agent roles than the agents themselves for a given communication model. This issue reflects this methodology’s degree of abstraction since a role defining as an abstract representation of high level behavioural allows generalising the best possible scenarios which can be found in a given multi-robot system.
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Slovák, Juraj, Markus Melicher, Matej Šimovec, and Ján Vachálek. "Vision and RTLS Safety Implementation in an Experimental Human—Robot Collaboration Scenario." Sensors 21, no. 7 (April 1, 2021): 2419. http://dx.doi.org/10.3390/s21072419.
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Human–robot collaboration is becoming ever more widespread in industry because of its adaptability. Conventional safety elements are used when converting a workplace into a collaborative one, although new technologies are becoming more widespread. This work proposes a safe robotic workplace that can adapt its operation and speed depending on the surrounding stimuli. The benefit lies in its use of promising technologies that combine safety and collaboration. Using a depth camera operating on the passive stereo principle, safety zones are created around the robotic workplace, while objects moving around the workplace are identified, including their distance from the robotic system. Passive stereo employs two colour streams that enable distance computation based on pixel shift. The colour stream is also used in the human identification process. Human identification is achieved using the Histogram of Oriented Gradients, pre-learned precisely for this purpose. The workplace also features autonomous trolleys for material supply. Unequivocal trolley identification is achieved using a real-time location system through tags placed on each trolley. The robotic workplace’s speed and the halting of its work depend on the positions of objects within safety zones. The entry of a trolley with an exception to a safety zone does not affect the workplace speed. This work simulates individual scenarios that may occur at a robotic workplace with an emphasis on compliance with safety measures. The novelty lies in the integration of a real-time location system into a vision-based safety system, which are not new technologies by themselves, but their interconnection to achieve exception handling in order to reduce downtimes in the collaborative robotic system is innovative.
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Gong, Chunhe, Jingxia Yuan, and Jun Ni. "A Self-Calibration Method for Robotic Measurement System." Journal of Manufacturing Science and Engineering 122, no. 1 (June 1, 1999): 174–81. http://dx.doi.org/10.1115/1.538916.
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Robot calibration plays an increasingly important role in manufacturing. For robot calibration on the manufacturing floor, it is desirable that the calibration technique be easy and convenient to implement. This paper presents a new self-calibration method to calibrate and compensate for robot system kinematic errors. Compared with the traditional calibration methods, this calibration method has several unique features. First, it is not necessary to apply an external measurement system to measure the robot end-effector position for the purpose of kinematic identification since the robot measurement system has a sensor as its integral part. Second, this self-calibration is based on distance measurement rather than absolute position measurement for kinematic identification; therefore the calibration of the transformation from the world coordinate system to the robot base coordinate system, known as base calibration, is not necessary. These features not only greatly facilitate the robot system calibration, but also shorten the error propagation chain, therefore, increase the accuracy of parameter estimation. An integrated calibration system is designed to validate the effectiveness of this calibration method. Experimental results show that after calibration there is a significant improvement of robot accuracy over a typical robot workspace. [S1087-1357(00)01301-0]
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Cruz Ulloa, Christyan, Guillermo Prieto Sánchez, Antonio Barrientos, and Jaime Del Cerro. "Autonomous Thermal Vision Robotic System for Victims Recognition in Search and Rescue Missions." Sensors 21, no. 21 (November 4, 2021): 7346. http://dx.doi.org/10.3390/s21217346.
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Technological breakthroughs in recent years have led to a revolution in fields such as Machine Vision and Search and Rescue Robotics (SAR), thanks to the application and development of new and improved neural networks to vision models together with modern optical sensors that incorporate thermal cameras, capable of capturing data in post-disaster environments (PDE) with rustic conditions (low luminosity, suspended particles, obstructive materials). Due to the high risk posed by PDE because of the potential collapse of structures, electrical hazards, gas leakage, etc., primary intervention tasks such as victim identification are carried out by robotic teams, provided with specific sensors such as thermal, RGB cameras, and laser. The application of Convolutional Neural Networks (CNN) to computer vision is a breakthrough for detection algorithms. Conventional methods for victim identification in these environments use RGB image processing or trained dogs, but detection with RGB images is inefficient in the absence of light or presence of debris; on the other hand, developments with thermal images are limited to the field of surveillance. This paper’s main contribution focuses on implementing a novel automatic method based on thermal image processing and CNN for victim identification in PDE, using a Robotic System that uses a quadruped robot for data capture and transmission to the central station. The robot’s automatic data processing and control have been carried out through Robot Operating System (ROS). Several tests have been carried out in different environments to validate the proposed method, recreating PDE with varying conditions of light, from which the datasets have been generated for the training of three neural network models (Fast R-CNN, SSD, and YOLO). The method’s efficiency has been tested against another method based on CNN and RGB images for the same task showing greater effectiveness in PDE main results show that the proposed method has an efficiency greater than 90%.
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Lee, Yi-Liang, Kai-Jo Chiang, Chi-Kung Lin, Tai-Kuang Chao, Mu-Hsien Yu, Yung-Liang Liu, and Yu-Chi Wang. "Robotic Hysterectomy with Ureter Identification and Uterine Artery Ligation for Benign Gynecological Conditions: An Early-Year Single-Center Experience." Diagnostics 13, no. 10 (May 20, 2023): 1809. http://dx.doi.org/10.3390/diagnostics13101809.
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The use and application of robotic systems with a high-definition, three-dimensional vision system and advanced EndoWrist technology have become widespread. We sought to share our clinical experience with ureter identification and preventive uterine artery ligation in robotic hysterectomy. The records of patients undergoing robotic hysterectomy between May 2014 and December 2015, including patient preoperative characteristics, operative time, and postoperative outcomes, were analyzed. We evaluated the feasibility and safety of using early ureteral identification and preventive uterine artery ligation in robotic hysterectomy in patients with benign gynecological conditions. Overall, 49 patients diagnosed with benign gynecological conditions were evaluated. The mean age of the patients and mean uterine weight were 46.2 ± 5.3 years and 348.7 ± 311.8 g, respectively. Robotic hysterectomy achieved satisfactory results, including a short postoperative hospital stay (2.7 ± 0.8 days), low conversion rate (n = 0), and low complication rate (n = 1; 2%). The average estimated blood loss was 109 ± 107.2 mL. Our results suggest that robotic hysterectomy using early ureteral identification and preventive uterine artery ligation is feasible and safe in patients with benign gynecological conditions.
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BENSACI, Chaima, Youcef ZENNIR, and Marry Ann LUNDTEIGEN. "Risk Identification of Robotic Systems through the Application of System-Theoretic Process Analysis." Algerian Journal of Signals and Systems 9, no. 2 (June 30, 2024): 107–13. http://dx.doi.org/10.51485/ajss.v9i2.217.
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Autonomous multi-mobile robots are becoming increasingly prevalent in various applications, ranging from industrial automation to healthcare and logistics. While these robots offer enhanced efficiency and productivity, their operation introduces many safety challenges. In this paper, the application of System-Theoretic Process Analysis (STPA) is proposed as a systematic approach to identify and mitigate risks associated with the main features of autonomous multi-mobile robots. This approach is illustrated using a case study concerning a transportation task of hazardous products within a robotic analysis laboratory. Through a structured analysis process, STPA enables the identification of unsafe control actions, the establishment of safety constraints also the generation of safety requirements. The ultimate goal is to improve the autonomous attribute of mobile robots, so on ensuring their operational safety in high-risk environments.
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Cruz Ulloa, Christyan, David Orbea, Jaime del Cerro, and Antonio Barrientos. "A Portable Artificial Robotic Nose for CO2 Concentration Monitoring." Machines 12, no. 2 (February 5, 2024): 108. http://dx.doi.org/10.3390/machines12020108.
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The technological advancements in sensory systems and robotics over the past decade have facilitated the innovation of centralized systems for optimizing resource utilization and monitoring efficiency in inspection applications. This paper presents a novel system designed for gas concentration sensing in environments by implementing a modular artificial nose (emulating the inhalation and exhalation process) equipped with a strategically designed air capture centralization system based on computational fluid dynamics analysis (CFD). The system incorporates three gas identification sensors distributed within the artificial nose, and their information is processed in real-time through embedded systems. The artificial nose is hardware–software integrated with a quadruped robot capable of traversing the environment to collect samples, maximizing coverage area through its mobility and locomotion capabilities. This integration provides a comprehensive perspective on gas distribution in a specific area, enabling the efficient detection of substances in the surrounding environment. The robotic platform employs a graphical interface for real-time gas concentration data map visualization. System integration is achieved using the Robot Operating System (ROS), leveraging its modularity and flexibility advantages. This innovative robotic approach offers a promising solution for enhanced environmental inspection and monitoring applications.
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Clitan, Iulia, Vlad Mureşan, Andrei Florin Clitan, and Mihail Abrudean. "Fractional Order Model Identification for a Billet Unloading Robotic Arm." Applied Mechanics and Materials 841 (June 2016): 234–39. http://dx.doi.org/10.4028/www.scientific.net/amm.841.234.
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This paper presents a fractional model identification for a billet unloading robotic arm’s positioning system. First, an integer order model is obtained using a graphical identification method based on a set of experimental data. The experimental data represents the robotic arm’s position, measured using an encoder, at a constant billet displacement. The integer order model was obtained based on the overall performances of the measured robotic arm’s step response. The mean square error between the measured data and the model step response is high, thus, in order to decrease the error and to obtain a more accurate model, a fractional order model is determined using an iterative procedure.
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Li, Jie, Beibei Li, Linjie Dong, Xingsong Wang, and Mengqian Tian. "Weld Seam Identification and Tracking of Inspection Robot Based on Deep Learning Network." Drones 6, no. 8 (August 20, 2022): 216. http://dx.doi.org/10.3390/drones6080216.
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The weld seams of large spherical tank equipment should be regularly inspected. Autonomous inspection robots can greatly enhance inspection efficiency and save costs. However, the accurate identification and tracking of weld seams by inspection robots remains a challenge. Based on the designed wall-climbing robot, an intelligent inspection robotic system based on deep learning is proposed to achieve the weld seam identification and tracking in this study. The inspection robot used mecanum wheels and permanent magnets to adsorb metal walls. In the weld seam identification, Mask R-CNN was used to segment the instance of weld seams. Through image processing combined with Hough transform, weld paths were extracted with a high accuracy. The robotic system efficiently completed the weld seam instance segmentation through training and learning with 2281 weld seam images. Experimental results indicated that the robotic system based on deep learning was faster and more accurate than previous methods, and the average time of identifying and calculating weld paths was about 180 ms, and the mask average precision (AP) was about 67.6%. The inspection robot could automatically track seam paths, and the maximum drift angle and offset distance were 3° and 10 mm, respectively. This intelligent weld seam identification system will greatly promote the application of inspection robots.
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Lee, J. X., and G. Vukovich. "The dynamic fuzzy logic system: Nonlinear system identification and application to robotic manipulators." Journal of Robotic Systems 14, no. 6 (June 1997): 391–405. http://dx.doi.org/10.1002/(sici)1097-4563(199706)14:6<391::aid-rob2>3.0.co;2-j.
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Hussain, Irfan, Ahmad Albalasie, Mohammad I. Awad, and Dongming Gan. "Modeling, Identification, and Control of a Discrete Variable Stiffness Actuator (DVSA)." Actuators 8, no. 3 (June 27, 2019): 50. http://dx.doi.org/10.3390/act8030050.
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A branch of robotics, variable impedance actuation, along with one of its subfields variable stiffness actuation (VSA) targets the realization of complaint robotic manipulators. In this paper, we present the modeling, identification, and control of a discrete variable stiffness actuator (DVSA), which will be developed for complaint manipulators in the future. The working principle of the actuator depends on the involvement of series and parallel springs. We firstly report the conceptual design of a stiffness varying mechanism, and later the details of the dynamic model, system identification, and control techniques are presented. The dynamic parameters of the system are identified by using the logarithmic decrement algorithm, while the control schemes are based on linear quadratic control (LQR) and computed torque control (CTC), respectively. The numerical simulations are performed for the evaluation of each method, and results showed the good potentialities for the system. Future work includes the implementation of the presented approach on the hardware.
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Savanevych, Vadym, Sergii Khlamov, Oleksandr Briukhovetskyi, Tetiana Trunova, and Iryna Tabakova. "Mathematical Methods for an Accurate Navigation of the Robotic Telescopes." Mathematics 11, no. 10 (May 11, 2023): 2246. http://dx.doi.org/10.3390/math11102246.
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Accurate sky identification is one of the most important functions of an automated telescope mount. The more accurately the robotic telescope is navigated to the investigated part of the sky, the better the observations and discoveries made. In this paper, we present mathematical methods for accurate sky identification (celestial coordinates determination). They include the automatic selection of the reference stars, preliminary and full sky identification, as well as an interaction with international databases, which are a part of the astrometric calibration. All described methods help to receive accurately calculated astrometric data and use it for the positional calibration and better navigation of the automated telescope mount. The developed methods were successfully implemented in the Collection Light Technology (CoLiTec) software. Through its use, more than 1600 small solar system objects were discovered. It has been used in more than 700,000 observations and successful sky identifications, during which, five comets were discovered. Additionally, the accuracy indicators of the processing results of the CoLiTec software are provided in the paper, which shows benefits of the CoLiTec software and lower standard deviation of the sky identification in the case of low signal-to-noise ratios.
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Galin, R. R., V. V. Serebrennyj, G. K. Tevyashov, and A. A. Shiroky. "Human-robot Interaction in Collaborative Robotic Systems." Proceedings of the Southwest State University 24, no. 4 (February 4, 2021): 180–99. http://dx.doi.org/10.21869/2223-1560-2020-24-4-180-199.
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Purpose or research is to find solvable tasks for increasing the effectiveness of collaborative interaction between people and robots in ergatic robotic systems, or, in other words, in collaborative robotic systems. Methods. A comprehensive analysis of works published in highly rated peer-reviewed open-access scientific publications was carried out to achieve this goal. Main terms and concepts of collaborative robotics are described in § 1 and their current understanding in the research community is also described. The structure of workspaces in interaction zone of a person and robot is described. The criteria for assigning robot to the class of collaborative ones are also described. The criteria for safe interaction of a person and robot in a single workspace is described in § 2. Various grounds for classifying human-robot interactions in collaborative RTAs are described in § 3. Results. A significant part of published works about collaborative robotics is devoted to the organization of safe man and robot interaction. Less attention is paid to the effectiveness improvement of such interaction. An up-to-date task in the problem of efficiency improvement of collaborative robotic systems is the identification of tasks that have already been solved in other areas - in particular, in the field of organizational systems management. The possibility of using the term "team" for collaborative robots in a collaborative PTC is stated in § 4. A formal problem setting of optimal distribution in teamwork of collaborative robots, similar to the problem of heterogeneous team formation in the theory of organizational systems management is proposed in § 5. Conclusions. Proposed task setting of optimal distribution of works in collaborative robots’ team shows possibility of using results obtained in group of mathematical models of commands formation and functioning for control of collaborative robotic systems in order to increase efficiency of people and robots interaction. It is prospectively to continue the search for adapting models and governance mechanisms to the theory of organizational system management and integrated activities methodology.
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Gong, Chunhe, Jingxia Yuan, and Jun Ni. "Nongeometric error identification and compensation for robotic system by inverse calibration." International Journal of Machine Tools and Manufacture 40, no. 14 (November 2000): 2119–37. http://dx.doi.org/10.1016/s0890-6955(00)00023-7.
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Abd Samad, Md Fahmi, and Farah Ayiesya Zainuddin. "Single parent mating in genetic algorithm for real robotic system identification." IAES International Journal of Artificial Intelligence (IJ-AI) 12, no. 1 (March 1, 2023): 201. http://dx.doi.org/10.11591/ijai.v12.i1.pp201-208.
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<span lang="EN-US">System identification (SI) is a method of determining a mathematical model for a system given a set of input-output data. A representation is made using a mathematical model based on certain specified assumptions. In SI, model structure selection is a step where a model structure perceived as an adequate system representation is selected. A typical rule is that the final model must have a good balance between parsimony and accuracy. As a popular search method, genetic algorithm (GA) is used for selecting a model structure. However, the optimality of the final model depends much on the effectiveness of GA operators. This paper presents a mating technique named single parent mating (SPM) in GA for use in a real robotic SI. This technique is based on the chromosome structure of the parents such that a single parent is sufficient in achieving mating that eases the search for the optimal model. The results show that using three different objective functions (Akaike information criterion, Bayesian information criterion and parameter magnitude–based information criterion 2) respectively, GA with the mating technique is able to find more optimal models than without the mating technique. Validations show that the selected models using the mating technique are acceptable.</span>
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Anufriiev, V. V., O. O. Levchenko, Ye V. Levchenko, V. A. Chekubasheva, O. V. Glukhov, and O. B. Galat. "Perspective of Creating Low-Cost Medical Assistant Robot Based on Waffle PI4 Platform with Palm Vein Pattern Scanner." Visnyk NTUU KPI Seriia - Radiotekhnika Radioaparatobuduvannia, no. 98 (December 30, 2024): 46–54. https://doi.org/10.20535/radap.2024.98.46-54.
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The purpose of this study is to develop a set of modifications for the TurtleBot 3 Waffle Pi robotic platform. One of the key achievements of this work is the creation of a biometric identification system based on the venous pattern of the palm. The principle of operation of the identification system is based on the use of infrared radiation absorbed by hemoglobin in the venous system of the palm. The absorbed radiation creates a clear pattern that can be captured using a camera without an infrared filter. The resulting image is pre-processed to reduce noise and unify with other images for further use in training a convolutional neural network used for patient identification. This identification method allows for high-speed and accurate patient identification, even with dirt or scratches on the palm. The described modifications are aimed at expanding the capabilities of the platform for military medical applications. By integrating these modifications into the TurtleBot 3 Waffle Pi robotic platform, military and civilian hospitals can improve their ability to provide timely and accurate medical care to those in need.
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Beiderman, Yevgeny, Mark Kunin, Eli Kolberg, Ilan Halachmi, Binyamin Abramov, Rafael Amsalem, and Zeev Zalevsky. "Automatic solution for detection, identification and biomedical monitoring of a cow using remote sensing for optimised treatment of cattle." Journal of Agricultural Engineering 45, no. 4 (December 21, 2014): 153. http://dx.doi.org/10.4081/jae.2014.418.
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In this paper we show how a novel photonic remote sensing system assembled on a robotic platform can extract vital biomedical parameters from cattle including their heart beating, breathing and chewing activity. The sensor is based upon a camera and a laser using selfinterference phenomena. The whole system intends to provide an automatic solution for detection, identification and biomedical monitoring of a cow. The detection algorithm is based upon image processing involving probability map construction. The identification algorithms involve well known image pattern recognition techniques. The sensor is used on top of an automated robotic platform in order to support animal decision making. Field tests and computer simulated results are presented.
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Quevedo, Fernando, Jorge Muñoz, Juan Alejandro Castano Pena, and Concepción A. Monje. "3D Model Identification of a Soft Robotic Neck." Mathematics 9, no. 14 (July 13, 2021): 1652. http://dx.doi.org/10.3390/math9141652.
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Soft robotics is becoming an emerging solution to many of the problems in robotics, such as weight, cost and human interaction. In order to overcome such problems, bio-inspired designs have introduced new actuators, links and architectures. However, the complexity of the required models for control has increased dramatically and geometrical model approaches, widely used to model rigid dynamics, are not enough to model these new hardware types. In this paper, different linear and non-linear models will be used to model a soft neck consisting of a central soft link actuated by three motor-driven tendons. By combining the force on the different tendons, the neck is able to perform a motion similar to that of a human neck. In order to simplify the modeling, first a system input–output redefinition is proposed, considering the neck pitch and roll angles as outputs and the tendon lengths as inputs. Later, two identification strategies are selected and adapted to our case: set membership, a data-driven, nonlinear and non-parametric identification strategy which needs no input redefinition; and Recursive least-squares (RLS), a widely recognized identification technique. The first method offers the possibility of modeling complex dynamics without specific knowledge of its mathematical representation. The selection of this method was done considering its possible extension to more complex dynamics and the fact that its impact in soft robotics is yet to be studied according to the current literature. On the other hand, RLS shows the implication of using a parametric and linear identification in a nonlinear plant, and also helps to evaluate the degree of nonlinearity of the system by comparing the different performances. In addition to these methods, a neural network identification is used for comparison purposes. The obtained results validate the modeling approaches proposed.
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Kuzmych, Khrystyna, Carolina Sassorossi, Dania Nachira, Maria Teresa Congedo, Stefano Margaritora, and Elisa Meacci. "Fully Dual-Portal Robotic-Assisted Thoracic Surgery (F-DRATS) and Indocyanine Green-Navigated Segmentectomy." Surgical Techniques Development 13, no. 3 (August 19, 2024): 294–300. http://dx.doi.org/10.3390/std13030022.
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Background: In the landscape of thoracic surgery, innovation continually drives progress, offering novel approaches to address complex pathologies while prioritizing patient well-being. Dual-port robotic-assisted thoracic surgery (DRATS) represents a new frontier in this evolution. In this report, we describe our experience with the fully dual-port robotic-assisted thoracic surgery (F-DRATS) approach for segmentectomy with the indocyanine green intersegmental plane identification. Methods: We define as F-DRATS the robotic thoracic surgery performed by two intercostal incisions without rib spreading, using the robotic camera, robotic dissecting instruments, and exclusively robotic staplers. We herein describe our F-DRATS approach in lingulectomy and lymphadenectomy of stations 5, 6, 7, and 10 using the da Vinci Surgical System. Results: The patient’s postoperative course was uneventful with the chest tube removed on the second postoperative day. The final pathological analysis confirmed a low-grade malignant potential adenocarcinoma, with a main diameter of 1.1 cm, at 3 cm from the lung margins. Conclusions: This is the first description in the literature of a F-DRATS lingulectomy with ICG intersegmental plane identification.
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Nillahoot, Nantida, Branesh M. Pillai, Bibhu Sharma, Chumpon Wilasrusmee, and Jackrit Suthakorn. "Interactive 3D Force/Torque Parameter Acquisition and Correlation Identification during Primary Trocar Insertion in Laparoscopic Abdominal Surgery: 5 Cases." Sensors 22, no. 22 (November 19, 2022): 8970. http://dx.doi.org/10.3390/s22228970.
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Laparoscopic procedures have become indispensable in gastrointestinal surgery. As a minimally invasive process, it begins with primary trocar insertion. However, this step poses the threat of injuries to the gastrointestinal tract and blood vessels. As such, the comprehension of the insertion process is crucial to the development of robotic-assisted/automated surgeries. To sustain robotic development, this research aims to study the interactive force/torque (F/T) behavior between the trocar and the abdomen during the trocar insertion process. For force/torque (F/T) data acquisition, a trocar interfaced with a six-axis F/T sensor was used by surgeons for the insertion. The study was conducted during five abdominal hernia surgical cases in the Department of Surgery, Faculty of Medicine, Ramathibodi Hospital, Mahidol University. The real-time F/T data were further processed and analyzed. The fluctuation in the force/torque (F/T) parameter was significant, with peak force ranging from 16.83 N to 61.86 N and peak torque ranging from 0.552 Nm to 1.76 Nm. The force parameter was observed to positively correlate with procedural time, while torque was found to be negatively correlated. Although during the process a surgeon applied force and torque in multiple axes, for a robotic system, the push and turn motion in a single axis was observed to be sufficient. For minimal tissue damage in less procedural time, a system with low push force and high torque was observed to be advantageous. These understandings will eventually benefit the development of computer-assisted or robotics technology to improve the outcome of the primary trocar insertion procedure.
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Hu, Jun, Phil Miller, Michael Lomnitz, Saurabh Farkya, Emre Yilmaz, Aswin Raghavan, David Zhang, and Michael Piacentino. "Tools Identification By On-Board Adaptation of Vision-and-Language Models." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 21 (March 24, 2024): 23799–801. http://dx.doi.org/10.1609/aaai.v38i21.30569.
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A robotic workshop assistant has been a long-standing grand challenge for robotics, speech, computer vision, and artificial intelligence (AI) research. We revisit the goal of visual identification of tools from human queries in the current era of Large Vision-and-Language models (like GPT-4). We find that current off-the-shelf models (that are trained on internet images) are unable to overcome the domain shift and unable to identify small, obscure tools in cluttered environments. Furthermore, these models are unable to match tools to their intended purpose or affordances. We present a novel system for online domain adaptation that can be run directly on a small on-board processor. The system uses Hyperdimensional Computing (HD), a fast and efficient neuromorphic method. We adapted CLIP to work with explicit ("I need the hammer") and implicit purpose-driven queries ("Drive these nails"), and even with depth images as input. This demo allows the user to try out various real tools and interact via free-form audio.
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Wang, Cheng-Chi, and Yong-Quan Zhu. "Identification and Machine Learning Prediction of Nonlinear Behavior in a Robotic Arm System." Symmetry 13, no. 8 (August 6, 2021): 1445. http://dx.doi.org/10.3390/sym13081445.
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In this study, the subject of investigation was the dynamic double pendulum crank mechanism used in a robotic arm. The arm is driven by a DC motor though the crank system and connected to a fixed side with a mount that includes a single spring and damping. Robotic arms are now widely used in industry, and the requirements for accuracy are stringent. There are many factors that can cause the induction of nonlinear or asymmetric behavior and even excite chaotic motion. In this study, bifurcation diagrams were used to analyze the dynamic response, including stable symmetric orbits and periodic and chaotic motions of the system under different damping and stiffness parameters. Behavior under different parameters was analyzed and verified by phase portraits, the maximum Lyapunov exponent, and Poincaré mapping. Firstly, to distinguish instability in the system, phase portraits and Poincaré maps were used for the identification of individual images, and the maximum Lyapunov exponents were used for prediction. GoogLeNet and ResNet-50 were used for image identification, and the results were compared using a convolutional neural network (CNN). This widens the convolutional layer and expands pooling to reduce network training time and thickening of the image; this deepens the network and strengthens performance. Secondly, the maximum Lyapunov exponent was used as the key index for the indication of chaos. Gaussian process regression (GPR) and the back propagation neural network (BPNN) were used with different amounts of data to quickly predict the maximum Lyapunov exponent under different parameters. The main finding of this study was that chaotic behavior occurs in the robotic arm system and can be more efficiently identified by ResNet-50 than by GoogLeNet; this was especially true for Poincaré map diagnosis. The results of GPR and BPNN model training on the three types of data show that GPR had a smaller error value, and the GPR-21 × 21 model was similar to the BPNN-51 × 51 model in terms of error and determination coefficient, showing that GPR prediction was better than that of BPNN. The results of this study allow the formation of a highly accurate prediction and identification model system for nonlinear and chaotic motion in robotic arms.
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Michal, Martin, Petr Valha, and Miloš Velemínský. "Sentinel lymph node mapping in endometrial cancer – robotic vs. laparoscopic detection system." Česká gynekologie 88, no. 3 (June 21, 2023): 157–61. http://dx.doi.org/10.48095/cccg2023157.
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Summary: Objective: Comparison of systems to detect sentinel lymph node in endometrial carcinoma using indocyanine green. Robotic Firefly Da Vinci fluorescence imaging system (Intuitive Surgical Inc., Sunnyvale, CA, USA) vs. laparoscopic Novadaq Pinpoint near-infrared imaging system (Novadaq, Ontario, Canada). Material and method: Fifteen patients with stage I endometrial cancer underwent sentinel lymph node biopsy after intracervical application of indocyanine green. For all of them, the detection was performed sequentially using both evaluated devices. The detection rate, identification match and extent of imaging of the lymphatic system were evaluated. Results: The detection rate of both systems verified on a set of patients was identical, the detected sentinel nodes were identical, and the lymphatic system was shown to the same extent. The quality of the display and overall user-friendliness is different due to the applied technologies. Conclusion: Both systems used in minimally invasive surgery provide excelent perioperative imaging of the lymphatic system. Key words: endometrial cancer – sentinel lymph node – indocyanine green – Da Vinci Firefly – Novadaq Pinpoint
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Liang, Fan, Li Li Yang, Shi Gang Cui, Li Zhao, Xing Li Wu, and Li Guo Tian. "System Identification of Beating Heart Medical Surgery Assisted Robot." Applied Mechanics and Materials 577 (July 2014): 1262–65. http://dx.doi.org/10.4028/www.scientific.net/amm.577.1262.
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The wide bandwidth and high amplitude feature of the beating heart motion makes surgeon hard to achieve the coronary artery bypass graph surgery on his or her own. The robot could help to cancel the relative motion between the end effecter of the robotic tool and certain point on the heart surface. Therefore a stationary operation screen could be used for the surgeon. The precise robot modeling is the prerequisite for tracking control algorithm. In the paper, we process the input and output data by using the nonlinear optimization method to obtain the system model. Next, we discuss the system identification related problems and modify the model. Finally, a good system model is achieved.
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Sakalys, Paulius, Loreta Savulioniene, and Dainius Savulionis. "RESEARCH OF ROBOT - HUMANOID CONTROL METHODS USING HUMAN BODY MOTION RECOGNITION TOOLS." SOCIETY. INTEGRATION. EDUCATION. Proceedings of the International Scientific Conference 1 (May 19, 2022): 237–45. http://dx.doi.org/10.17770/sie2022vol1.6883.
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The aim of the research is to investigate and evaluate the repetition indices of the displacements of the robot‘s kinematic nodes, using the means of identification human body movements, using a real robotic system. The article presents an analysis of human body motion recognition tools, identifies typical application criteria that meet the requirements of robotic systems control, describes the developed physical research stand "Robot - humanoid": the robotic system is identified with the human body with two of nine-kinematic degrees of freedom hands and a two degree of freedom robotic mechanism replacing the head on which the environmental video surveillance equipment is mounted. The publication presents systematized experimental data and suggestions for the integration of research results into the process of students' practical - applied teaching in a contact or distance way.
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Ergen, Anıl, Burak Çabuk, Pınar Yıldırım, Mehmet Deniz Yener, Selçuk Kizir, Melih Çaklılı, İhsan Anık, and Savaş Ceylan. "Design and use of assistant robotic arm in endoscopic transnasal surgery." Neurosurgical Focus 57, no. 6 (December 1, 2024): E6. https://doi.org/10.3171/2024.9.focus24426.
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OBJECTIVE This study aimed to develop a robotic system with autonomous functionality for holding and manipulating the endoscope in endoscopic endonasal surgery. A cost-effective prototype was created with the goal of using robotic assistance and achieving a more efficient learning curve for endoscopic surgery. METHODS A Stewart platform–based endoscope holder and positioner robotic system, developed by the Mechatronics Engineering Department of Kocaeli University, was used in conjunction with 3D Slicer and Plus Toolkit open-source health technology software. Following initial configuration on a 3D skull model, the system was applied to a fresh-frozen cadaver. RESULTS The robotic system and its registration process proved feasible, allowing the robot to autonomously reach predetermined anatomical points during the nasal step of the surgery. Compared with a previous study by the same authors, the surgery duration was successfully shortened. The experiment yielded positive outcomes in both the artificial skull model and the cadaver. The robotic system effectively performed the nasal stage of the surgery. The integration of a robotic surgical arm in the endoscopic endonasal approach holds the potential to enhance the learning curve through shared experiences. The robot offers assistance to surgeons during the learning phase of the endoscopic endonasal approach, aiding in the identification of anatomical landmarks through preoperative planning. CONCLUSIONS This system may present advantages such as improved visualization, enhanced maneuverability, and reduced user fatigue compared with conventional methods. These findings show the potential of robotic assistance in endoscopic surgical techniques.
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Mentsiev, Adam. "Strategic integration of technology in precision agriculture." BIO Web of Conferences 84 (2024): 01026. http://dx.doi.org/10.1051/bioconf/20248401026.
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This research focuses on the strategic integration of advanced technologies in microclonal propagation for precision agriculture. The development of an automated system, incorporating computer vision, robotic manipulation, QR code identification, and cloud storage, aims to revolutionize the efficiency and precision of plant sorting processes. Computer vision facilitates early detection of viruses, while a moving platform and robotic arm enhance mobility and accuracy. The QR code system and cloud storage infrastructure enable seamless plant identification and dynamic data analysis. Challenges, including biological variability and technological obsolescence, are addressed through iterative learning and modular design. The research represents a transformative leap in agriculture, offering a promising avenue for sustainable and data-driven cultivation practices to meet the challenges of an evolving global food landscape.
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Dai, Yu, Yuan Xue, and Jianxun Zhang. "Milling State Identification Based on Vibration Sense of a Robotic Surgical System." IEEE Transactions on Industrial Electronics 63, no. 10 (October 2016): 6184–93. http://dx.doi.org/10.1109/tie.2016.2574981.
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Torres, S., and V. M. Becerra. "Nonlinear Identification of a Two Link Robotic System Using Dynamic Neural Networks." IFAC Proceedings Volumes 36, no. 16 (September 2003): 363–68. http://dx.doi.org/10.1016/s1474-6670(17)34788-2.
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Viola, Jairo, and Luis Angel. "Identification, control and robustness analysis of a robotic system using fractional control." IEEE Latin America Transactions 13, no. 5 (May 2015): 1294–302. http://dx.doi.org/10.1109/tla.2015.7111982.
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Blue, Ben, Elena Vayndorf, Matt Kaeberlein, and Jason Pitt. "A ROBOTIC SYSTEM FOR HIGH-THROUGHPUT AUTOMATED LIFESPAN ANALYSIS IN C. ELEGANS." Innovation in Aging 3, Supplement_1 (November 2019): S102. http://dx.doi.org/10.1093/geroni/igz038.383.
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Abstract Over the past decade, the identification of potential genetic and pharmacological modifiers of lifespan and age-related pathologies in C. elegans and other model organisms has yielded fruitful leads for follow-up investigation. A major limitation of such studies, however, is that they are often time-consuming and labor-intensive. The advent of affordable high-quality digital cameras, robotics systems, and 3D printers, as well as the decreasing costs of image storage and processing have allowed us to automate data capture and analysis at an unprecedented scale. To this end, our group developed a tool consisting of an unbiased, high-throughput, automated robotic system to perform genetic and pharmacological quantification of lifespan and health measures in C. elegans and related nematode species. The WormBot utilizes industry-standard, commercially available robotics components to position a digital camera over individual wells of standard 12-well culture plates, containing a small population of C. elegans per well. A high-resolution image is captured of each plate every 10 minutes throughout the course of the experiment. Our software processes the images for stabilization, compiles them into a time-lapse series for each well, and quantifies survival and mobility (paralysis) with minimal input. In addition, a short video is captured of each well once each day, to allow for quantitative analyses of activity and coordinated movement. We will describe this technology and present applications to screen genetic and pharmacological libraries in aging and age-related disease.
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Blinov, A. O., A. V. Borisov, L. V. Konchina, M. G. Kulikova, and K. S. Maslova. "Issues emerging in human musculoskeletal system simulation with mechanical and electromechanical rod structures." Power engineering: research, equipment, technology 24, no. 5 (December 9, 2022): 147–65. http://dx.doi.org/10.30724/1998-9903-2022-24-5-147-165.
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Based on the statistical analysis of publications and patents located in the RSCI database for the keywords «exoskeleton», «anthropomorphic robot», «bionic prosthesis», interest in the research topic has been established, expressed in a significant increase in publications in recent years. It was revealed that most of the models use absolutely solid links in the form of rods.GOAL. Identification and study of problems arising in the modeling of anthropomorphic robotic systems. METHODS. Methods of mathematical modeling, analysis, comparison with a biological prototype, robotics, theoretical mechanics, electromechanics were used. RESULTS. The problem of accuracy of modeling by rod robotic systems with absolutely rigid links, a link of the human musculoskeletal system, is considered. The relative error of the accuracy of approximation by rods of a human limb is calculated, a conclusion is made about a significant error in the modeling of links. The problem of evaluating the influence of a rotating rotor of an electric motor on a mechanism model is considered. Next, the model is considered taking into account the rotating rotor and gearbox. It has been established that when modeling anthropomorphic mechanisms with rods, the problem arises of the need to take into account the dynamics of drives. An electromechanical model of a link with a DC motor is proposed. A significant increase in energy costs during the movement of the link has been established, in comparison with the model of an ideal hinge, in which the required control moment is created, which is a problem. A partial solution of the identified problems is proposed using the model of a variable length link containing three sections. CONCLUSION. The study made it possible to identify problems that arise when modeling the human musculoskeletal system with rod robotic electromechanical systems with absolutely solid links.
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Ejofodomi, O'tega, and Godswill Ofualagba. "Subsea Crude Oil Spill Detection Using Robotic Systems." European Journal of Engineering Research and Science 4, no. 12 (December 27, 2019): 112–16. http://dx.doi.org/10.24018/ejers.2019.4.12.1684.
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Underwater Robotic Oil Spill Surveillance (UROSS) system provides constant and autonomous spill surveillance for subsea pipelines. M900 embedded Radio Frequency Identification tags and readers are used to identify pipeline section for surveillance. GY-521 gyrometer and XL-MaxSonar-WR1 ultrasound sensor are used for autonomous navigation. Spills are detected using a METS methane sensor. After spill detection, images of spill site are captured with a L3C-400 Micro Ultras-Miniature Color Camera and spill location is obtained using GPS. Spill Images and location are transmitted to a remote PC on the nearest off shore platform using an Xbee Pro 900HP wireless connection. An Ocean Signal rescueME Personal Beacon Locator transmits a 406 MHz distress signal via satellite to emergency services communicating the identification of a spill. Power analysis showed the system’s ability to remain submerged and to provide surveillance for 100 m sections of a subsea pipeline once every 24 hrs for a month, and can be increased to every hour for 51 months.
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Ejofodomi, O'tega, and Godswill Ofualagba. "Subsea Crude Oil Spill Detection Using Robotic Systems." European Journal of Engineering and Technology Research 4, no. 12 (December 27, 2019): 112–16. http://dx.doi.org/10.24018/ejeng.2019.4.12.1684.
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Underwater Robotic Oil Spill Surveillance (UROSS) system provides constant and autonomous spill surveillance for subsea pipelines. M900 embedded Radio Frequency Identification tags and readers are used to identify pipeline section for surveillance. GY-521 gyrometer and XL-MaxSonar-WR1 ultrasound sensor are used for autonomous navigation. Spills are detected using a METS methane sensor. After spill detection, images of spill site are captured with a L3C-400 Micro Ultras-Miniature Color Camera and spill location is obtained using GPS. Spill Images and location are transmitted to a remote PC on the nearest off shore platform using an Xbee Pro 900HP wireless connection. An Ocean Signal rescueME Personal Beacon Locator transmits a 406 MHz distress signal via satellite to emergency services communicating the identification of a spill. Power analysis showed the system’s ability to remain submerged and to provide surveillance for 100 m sections of a subsea pipeline once every 24 hrs for a month, and can be increased to every hour for 51 months.
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Huczala, Daniel, Petr Oščádal, Tomáš Spurný, Aleš Vysocký, Michal Vocetka, and Zdenko Bobovský. "Camera-Based Method for Identification of the Layout of a Robotic Workcell." Applied Sciences 10, no. 21 (October 30, 2020): 7679. http://dx.doi.org/10.3390/app10217679.
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In this paper, a new method for the calibration of robotic cell components is presented and demonstrated by identification of an industrial robotic manipulator’s base and end-effector frames in a workplace. It is based on a mathematical approach using a Jacobian matrix. In addition, using the presented method, identification of other kinematic parameters of a robot is possible. The Universal Robot UR3 was later chosen to prove the working principle in both simulations and experiment, with a simple repeatable low-cost solution for such a task—image analysis to detect tag markers. The results showing the accuracy of the system are included and discussed.
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Jinxing, Shen, Cui Hongxin, Feng Ke, Zhang Hong, and Li Huanliang. "Parameter Identification and Control Algorithm of Electrohydraulic Servo System for Robotic Excavator Based on Improved Hammerstein Model." Mathematical Problems in Engineering 2020 (May 23, 2020): 1–9. http://dx.doi.org/10.1155/2020/9216019.
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In view of the nonlinearity and time-varying characteristics of the electrohydraulic servo system of the robotic excavator, a nonlinear adaptive identification and control algorithm based on improved Hammerstein model is proposed. The Hammerstein algorithm model can approximate the nonlinear system with enough precision, but for the time-varying systems is not satisfactory. In order to compensate for the influence of time-varying factors, the fuzzy control module is designed to adaptively update the forgetting factor. The experimental results show that the improved Hammerstein model error is about 40.11% less than the classical Hammerstein model error. This proves that the improved Hammerstein model is feasible and effective to describe the electrohydraulic servo system of the robotic excavator.
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Chen, Dongdong, Peijiang Yuan, Tianmiao Wang, Ying Cai, and Haiyang Tang. "A Normal Sensor Calibration Method Based on an Extended Kalman Filter for Robotic Drilling." Sensors 18, no. 10 (October 16, 2018): 3485. http://dx.doi.org/10.3390/s18103485.
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To enhance the perpendicularity accuracy in the robotic drilling system, a normal sensor calibration method is proposed to identify the errors of the zero point and laser beam direction of laser displacement sensors simultaneously. The procedure of normal adjustment of the robotic drilling system is introduced firstly. Next the measurement model of the zero point and laser beam direction on a datum plane is constructed based on the principle of the distance measurement for laser displacement sensors. An extended Kalman filter algorithm is used to identify the sensor errors. Then the surface normal measurement and attitude adjustments are presented to ensure that the axis of the drill bit coincides with the normal at drilling point. Finally, simulations are conducted to study the performance of the proposed calibration method and experiments are carried out on a robotic drilling system. The simulation and experimental results show that the perpendicularity of the hole is within 0.2°. They also demonstrate that the proposed calibration method has high accuracy of parameter identification and lays a basis for high-precision perpendicularity accuracy of drilling in the robotic drilling system.
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Roberts, Dustyn, Joseph Quacinella, and Joo H. Kim. "Energy expenditure of a biped walking robot: instantaneous and degree-of-freedom-based instrumentation with human gait implications." Robotica 35, no. 5 (January 14, 2016): 1054–71. http://dx.doi.org/10.1017/s0263574715000983.
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SUMMARYEnergy expenditure (EE) is an important criterion for design and control of biped walking robots. However, the cause-effect analyses enabled by total EE, which is lumped over a time duration and all system degrees-of-freedom (DOFs), are limited. In this study, robotic gait energetics is evaluated through a DOF-based instrumentation system designed for instantaneous evaluation of bidirectional current and applied voltage at each joint actuator. The instrumentation system includes a dual-module arrangement of buffers and attenuators, and accommodates and synchronizes the voltage and current measurements from multiple actuators. For illustrative purposes, this system is implemented at each DC servomotor in a biped robot, DARwIn-OP, to analyze the electrical EE rates for walking at various speeds. In addition, a DOF-based model of instantaneous human EE rate is employed to enable quantitative characterization of robotic walking EE relative to that of humans. The robot's instantaneous lower-body EE rates are consistent with its periodic walking cycle, and their relative trends between single and double support phases are analogous to those of humans. The robotic cost of transport (COT) curve as a function of normalized speed is also consistent with the human COT in terms of its convexity. Conversely, the contrasting distributions of EE throughout the robot and human DOFs and the robotic COT curve's considerably larger magnitudes, smaller speed ranges, and higher sensitivity to speed illustrate the energetic consequences of stable but inefficient static walking in the biped robot relative to the more efficient dynamic walking of humans. These energetic characteristics enable the identification of the joints and gait cycle phases associated with inefficiency in biped robotic gait, and reflect the noticeable differences in the system parameters (rigid and flat versus segmented feet) and gait control strategies (bent versus straight knees, instants of peak ankle actuator torques, static versus dynamic balance stability). The proposed general instrumentation provides a quantitative approach to benchmarking human gait as well as general guidelines for the development of energy-efficient walking robots.