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检索条件"机构=Robotics and Computer Engineering"

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TTCDist: Fast Distance Estimation From an Active Monocular Camera Using Time-to-Contact

TTCDist: Fast Distance Estimation From an Active Monocular C...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Levi Burner Nitin J. Sanket Cornelia Fermüller Yiannis Aloimonos Perception and Robotics Group Electrical and Computer Engineering University of Maryland College Park Robotics Engineering Worcester Polytechnic Institute Perception and Robotics Group University of Maryland Institute for Advanced Computer Studies University of Maryland College Park

Distance estimation from vision is fundamental for a myriad of robotic applications such as navigation, manipu-lation, and planning. Inspired by the mammal's visual system, which gazes at specific objects, we develop two novel constraints relating time-to-contact, acceleration, and distance that we call the $\tau$ -constraint and $\Phi$ -constraint. They allow an active (moving) camera to estimate depth efficiently and accurately while using only a small portion of the image. The constraints are applicable to range sensing, sensor fusion, and visual servoing. We successfully validate the proposed constraints with two experiments. The first applies both constraints in a trajectory estimation task with a monocular camera and an Inertial Measurement Unit (IMU). Our methods achieve 30-70% less average trajectory error while running $25\times$ and $6.2\times$ faster than the popular Visual-Inertial Odometry methods VINS-Mono and ROVIO respectively. The second experiment demonstrates that when the constraints are used for feedback with efference copies the resulting closed loop system's eigenvalues are invariant to scaling of the applied control signal. We believe these results indicate the $\tau$ and $\Phi$ constraint's potential as the basis of robust and efficient algorithms for a multitude of robotic applications.

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Intelligent Accident Recognition and Notification System using Hybrid Deep Learning and IoT 4

Intelligent Accident Recognition and Notification System usi...

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4th International Conference on Soft Computing for Security Applications, ICSCSA 2024

作者： Sathish Kumar, P. Singh Rawat, Ramesh Shrimali, Manish Parikh, Swapnil Patil, Harshal Maranan, Ramya United Institute of Technology Department of Robotics & Automation Tamil Nadu Coimbatore641020 India Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun248 002 India Department of Computer Science and IT Rajasthan Udaipur313 003 India Parul Institute of Engineering and Technology Parul University Department of Computer Science and Engineering Gujarat 391760 India Symbiosis Institute of Technology Symbiosis International Deemed University Computer Science and Engineering Maharashtra Pune412 115 India Saveetha School of Engineering SIMATS Department of Research and Innovation Tamil Nadu Chennai602105 India

ISBN: (纸本)9798331515720

Ensuring the safety of individuals should be a top priority. Everyone wants to return home safely. Many riders continue to disregard safety constraints, increasing the chance of accidents that result in death. It is critical to incorporate the latest technology into road monitoring systems to make cities smarter and to ensure rider safety. For this research, Deep Learning (DL) and the Internet of Things (IoT) were chosen for effective road surveillance and alert systems. The primary goal of the study is to detect and inform riders about accidents that occur along their path and to provide details about the location of the detected accident. Additionally, the system provides the vehicle's speed. To identify automobile accidents in the footage, a hybrid DL model that includes Convolutional Neural Network-Bidirectional Long Short-Term Memory (CNN-Bi-LSTM) is suggested. For the model's training, both accident and non-Accident data were collected. The model is evaluated using three metrics: Accuracy, loss, and execution time. The next step is to upload the recommended model to the ThingSpeak cloud. A Graphical User Interface (GUI) is being created in the ThingSpeak cloud. The GUI displays the vehicle's speed, accident images, and the precise location of the accident scene using the Raspberry Pi, speed sensor, Pi-camera, and Global Positioning System (GPS) module. An LED is also integrated into the GUI to alert the user. A real-world test is conducted on the designed system. The proposed solution has many advantages and will ensure driver safety. © 2024 IEEE.

关键词： Graphical user interfaces

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Design and Analysis of a Novel Hybrid Grasping Mode Microgripper for High Precision Tasks 9

Design and Analysis of a Novel Hybrid Grasping Mode Microgri...

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9th IEEE International Women in engineering (WIE) Conference on Electrical and computer engineering, WIECON-ECE 2023

作者： Das, Tilok Kumar Shahrear, Rifat Das, Arpita Shirinzadeh, Bijan Dept. of Mechanical Engineering Chattogram Bangladesh Temple University Dept. of Electrical and Computer Engineering PhiladelphiaPA United States Monash University Robotics and Mechatronics Research Laboratory Dept. of Mechanical and Aerospace Engineering MelbourneVIC Australia

ISBN: (纸本)9798350319651

This paper represents a novel piezoelectric actuated flexure-based compliant microgripper which can perform both parallel and angular grasping regardless of the geometric surface of the objects. Two compliant bridge-type mechanisms along with two symmetrical microgripper jaws at the end of the two side arms are accommodated to construct the microgripper. The two side arms of the microgripper act as lever-type amplification mechanisms. Simultaneous actuation of two bridge-type mechanisms is needed to perform linearized parallel grasping. The symmetric design is adopted to maintain better stability. The Finite Element Analysis (FEA) has been performed to evaluate the performance of the microgripper. FEA shows that each jaw of the microgripper can achieve a displacement of 141.72 μm resulting in a total displacement of 283.44 μm with an amplification ratio of 10.7 and 0.715% parasitic motion in y-direction of the X -axis displacement during parallel grasping. Also, each jaw can achieve a displacement of 283.88 μm which results in a total displacement of 567.76 μm with an amplification ratio of 21.5 and 5.17 mrad angular rotation about the Z-axis during angular grasping. The FEA suggests that the microgripper is capable of both parallel and angular grasping/releasing tasks. © 2023 IEEE.

关键词： Piezoelectric actuators

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Development and Evaluation of a Cost-effective IMU System for Gait Analysis: Comparison with Vicon and VideoPose3D Algorithms

Development and Evaluation of a Cost-effective IMU System fo...

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作者： Wilhelm, Nikolas Haddadin, Sami Micheler, Carina M. Lang, Jan J. Hinterwimmer, Florian Schaack, Victor Smits, Ricardo Burgkart, Rainer Department of Orthopedics and Sports Orthopedics Klinikum Rechts der Isar School of Medicine and Munich Institute of Robotics and Machine Intelligence Department of Electrical and Computer Engineering Technical University of Munich Munich Germany Munich Institute of Robotics and Machine Intelligence Department of Electrical and Computer Engineering Technical University of Munich Munich Germany Department of Orthopedics and Sports Orthopedics Klinikum Rechts der Isar School of Medicine Munich Germany

This study aimed to develop and evaluate a costeffective Inertial Measurement Unit (IMU) system for gait analysis, comparing its performance with the Vicon system and the VideoPose3D algorithm. The system comprises five calibrated sensors and a mobile app to measure lower body orientation during gait and stair climbing. Eight healthy participants were involved in the experiment, each performing ten repetitions to analyze hip and knee flexion angles. The IMU system demonstrated significantly lower mean square error than deep learning-based approaches and comparable results to the Vicon system, indicating its potential for clinical and research applications. © 2023 the author(s), published by Walter de Gruyter Berlin/Boston.

关键词： Gait analysis

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Traffic Signs Detection System Using YOLO (You Only Look Once) That Provides Notification

Traffic Signs Detection System Using YOLO (You Only Look Onc...

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Smart Mechatronics (ICSMech), IEEE International Conference on

作者： Yosua Setiawan Muhammad Nurul Puji Winda Astuti Computer Engineering Department Automotive & Robotics Program BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350368918

ISBN: (纸本)9798350368925

Road accidents have become a problem for many road users in many countries. It may affect human daily activity and tasks, potentially influencing productivity and safety. Therefore, reducing road accidents as swiftly and effectively as possible is critical. For this reason, a Traffic signs detection system has been developed in this work to improve road safety. The detection system can detect traffic signs on the road such as traffic lights, speed limits, and no U-turn signs, and then it will provide users with the corresponding text on an LCD and vibration feedback using a motor. Throughout this work, the You Only Look Once (YOLO) algorithm is proposed for detecting traffic signs on the road. Moreover, a camera is used to extract live videos which serve as an input for the Raspberry Pi 4 model B containing custom YOLOv5 and YOLOv8 models. The system then sends the output to an LCD, a vibration motor, and a radio frequency (RF) module as notifications for users. In the end, the performance of the proposed method has been collected and it is found to produce good accuracy within an inconsiderable amount of 1.677 images and 2.263 annotations. Therefore, the accuracy of 0.69 for YOLOv5 and 0.7 for YOLOv8 were obtained from the training and validation process. Furthermore, the system accurately detects the traffic signs on the road.

关键词： YOLO Vibrations Training Road accidents Accuracy Motors Liquid crystal displays Road safety Safety Videos

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Blockchain Technology and Artificial Intelligence's Future Applications in Cyber Security 3

Blockchain Technology and Artificial Intelligence's Future A...

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3rd International Conference on Advancement in Electronics and Communication engineering, AECE 2023

作者： Salama, Ramiz Al-Turjman, Sinem Altrjman, Chadi Al-Turjman, Fadi Gupta, Richa Yadav, Satya Prakash Vats, Satvik Ai and Robotics Institute Research Center for Ai and IoT Near East University Department of Computer Engineering Near East Boulevard TRNC Mersin 10 Nicosia99138 Turkey Ai and Robotics Institute Near East University Artificial Intelligence Engineering Dept Mersin10 Nicosia Turkey Waterloo University Department of Chemical Engineering ONN2L 3G1 Canada Raj Kumar Goel Institute of Technology Department of Electronics & Communication Engineering India Department of Computer Science and Engineering Greater Noida201306 India Graphic Era Hill University Department of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350330724

Artificial intelligence and blockchain are quickly integrating in daily life and business applications. When numerous information systems must access and analyze data in real-time in centralized systems and applications, such as healthcare, a bottleneck develops. This issue would be resolved by blockchain's decentralized database architecture, safe data storage, data exchange, and authentication. Additionally, AI can be present at the very top of the blockchain and produce insights from the shared data that is created and applied to forecasts. Blockchain is a cutting-edge Cybersecurity technology that creates chains by mutual consent between nodes that chronologically link new blocks to those previously stored in nodes. A number of industries, including banking, insurance, cybersecurity, forecasting, healthcare, and cryptocurrencies, among others, are growing more quickly as a result of technology convergence. The likelihood of these systems being hacked increases as more digital technologies are used and these businesses provide services. Blockchain technology and artificial intelligence can work together to create a strong defense against these dangers and security problems. We'll examine how blockchain and AI are merged in cybersecurity in this chapter. We'll go into more detail about how they help secure cyber-physical systems. © 2023 IEEE.

关键词： Blockchain

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Enhanced Soil Property Estimations from Earth Observation Data with Differential Evolution-Based Multi-Objective TSK Model 13

Enhanced Soil Property Estimations from Earth Observation Da...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Tsakiridis, Nikolaos L. Samarinas, Nikiforos Kalopesa, Eleni Theocharis, John B. Zalidis, George C. Aristotle University of Thessaloniki Spectra Lab Group Laboratory of Remote Sensing Spectroscopy and Gis Department of Agriculture Thessaloniki54124 Greece Aristotle University of Thessaloniki Automation and Robotics Laboratory Electrical and Computer Engineering Thessaloniki54124 Greece

ISBN: (纸本)9798350308365

This paper introduces a novel approach integrating Differential Evolution (DE) with multi-objective optimization techniques for enhancing Type-1 Takagi-Sugeno-Kang (TSK) fuzzy rule-based systems to attain both fair predictive performance and enhanced interpretability within the context of explainable artificial intelligence. The developed approach encodes the whole knowledge base into one chromosome and endeavors to concurrently optimize the prediction accuracy, the number of rules, and the selection of relevant input features. The methodology was tested on Earth observation data for the estimation of soil health parameters via infrared spectroscopy, and more concretely i) on the 2015 LUCAS topsoil dataset to predict three key soil properties (namely, soil organic carbon, clay content, and pH) from laboratory spectra, and ii) on a set of PRISMA hyperspectral images to predict soil organic carbon in a region of northern Greece. Compared to the classical Random Forest (RF) algorithm, our proposed learning algorithm attains a fair balance between accuracy and interpretability, and is statistically equivalent to RF in terms of accuracy. The findings underscore the potential of the proposed methodology in refining TSK models and its applicability in Earth observation-driven predictions, paving the way for both enhanced modeling accuracy and sparse feature selection. © 2024 IEEE.

关键词： Fuzzy rules

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Biomimetics in Photonic Systems

Biomimetics in Photonic Systems

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Pacific Rim Conference on Lasers and Electro-Optics (CLEO/Pacific Rim)

作者： Mable P. Fok Photonics and Soft Robotics Lab School of Electrical and Computer Engineering College of Engineering University of Georgia Athens GA USA

By learning and mimicking strategies of living organisms, effective photonics systems can be designed to tackle technology challenges. Biomimetics in microwave photonic systems and fiber-optic sensing systems for soft... 详细信息

ISBN: (数字)9798350372076

ISBN: (纸本)9798350372083

关键词： Biomimetics Masers Soft robotics Robot sensing systems Organisms Sensors Microwave photonics

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IoT Intervention in the monitoring of aquaponics metrics and control of input schedule

IoT Intervention in the monitoring of aquaponics metrics and...

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2024 International Conference on Smart Devices, ICSD 2024

作者： Malik, Pooja Malik, Praveen Kumar Ranjith Kumar, Gotte Bali, Jyoti S. Mahajan, Anshul Muhsen Hassan, M. Lovely Professional University School of Electronics and Electrical Engineering Punjab Phagwara India SR University School of Computer Science & Artificial Intelligence Warangal India Dept of Robotics and Automation Pune India The Islamic University Najaf Iraq

ISBN: (纸本)9798350394412

The extensive use of technology across several Modern civilization is clearly impacted by technology, with cutting-edge techniques and tools playing critical roles in sectors including healthcare, business, agriculture, and education. Processes have been transformed by these improvements, which have increased their dependability and efficiency. With the incorporation of technology, agriculture has made enormous strides, with techniques like aquaponics developing as extremely effective and sustainable systems. Aquaponics is a novel farming method that combines hydroponics (soilless plant cultivation) and aquaculture (fish farming) to grow vegetables and fish at the same time. But the performance of this incorporated system relies upon on careful observation of a number of vital elements, such as water high-quality, pH tiers, temperature, and dissolved oxygen levels. To keep the health and growth of both fish and flora in an aquaponics device, it's miles critical to hold perfect situations. This highlights the significance of technological intervention, especially via the integration of Internet of Things (IoT) era, and calls for precision in regulating the input time table for fish feed and plant vitamins. © 2024 IEEE.

关键词： Fish

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Active Multi-Modal Approach for Enhanced User Recognition in Social Robots

Active Multi-Modal Approach for Enhanced User Recognition in...

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Western New York Image Processing Workshop (WNYIPW)

作者： Ninad Kale Nalini Ratha Robotics Lab University at Buffalo Computer Science and Engineering University at Buffalo

The field of Human-Robot Interaction (HRI) is swiftly expanding, driven by notable advancements in artificial intelligence (AI). Humanoid robots, now capable of being equipped with advanced AI models, are being considered for a wide array of applications due to their ability to perform complex tasks and interact with humans in both natural and intelligent ways. In the domain of social robotics, the capability to selectively interact with authorized users is crucial for ensuring security and providing personalized user experiences. Unimodal user recognition methods, such as audio-based user recognition, are commonly used in social robots. However, these methods can be susceptible to ambient noise and might exhibit reduced accuracy. Although face recognition modality is often employed to enhance accuracy, the majority of audio-visual person recognition methods are trained on datasets with only a single user in the *** paper introduces a method for audio-visual user recognition with multiple users in the frame, utilizing an additional sound localization modality. The proposed method is evaluated using a dataset created from interactions between the social robot Pepper and multiple users. The results demonstrated that the proposed method significantly outperformed unimodal user recognition methods.

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