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A vision-Based Detection and Tracking Algorithm for a Child Monitoring robot

A Vision-Based Detection and Tracking Algorithm for a Child ...

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Asia-Pacific conference on Intelligent robot Systems (ACIRS)

作者： John Anthony C. Jose Justine Veronica Basco Jomar Kenneth Jolo Patrick Kenneth Yambao Melvin K. Cabatuan Argel A. Bandala Jose Martin Z. Maningo Elmer P. Dadios Electronics and Communications Engineering Department De La Salle University Manila Philippines Manufacturing Engineering and Management Department De La Salle University Manila Philippines

Accidents have been found to be one of the leading causes of both fatal and non-fatal injuries to children. though some accidents that occur are often unavoidable, more often than not these injuries can be prevented by giving the child proper attention. the researchers intend to address certain gaps in stationary monitoring solutions by adding abilities such as an insured way of continuously monitoring the test subject and a real time notification feature to a mobile spherical robot. this research presents the software division of a technological solution to child monitoring by developing a computer vision algorithm for following and monitoring children indoors utilizing an RGB-D camera. this algorithm will work hand in hand with a hardware design of a spherical robot that utilizes microcontrollers, RFID technology and GSM system. An Android application will also be created to provide the users the means of manually overriding the spherical robot, color calibration and location indicator as a part of the robot's notification system. the detection and tracking ability of the algorithm is tested by using objects with varying characteristics. the autonomous navigation testing of the robot is performed at two controlled test setups: living room and child's playroom.

关键词： Image color analysis computer vision Prototypes Cameras Color robot vision systems

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Digital model reconstruction through 3D Stereo Depth camera: a faster method exploiting robot poses 4

Digital model reconstruction through 3D Stereo Depth camera:...

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4th International conference on Industry 4.0 and Smart Manufacturing, ISM 2022

作者： Zaki, Ahmed Magdy Ahmed Carnevale, Marco Giberti, Hermes Schlette, Christian Università Degli Studi di Pavia Dipartimento di Ingegneria Industriale e Dell'Informazione via A. Ferrata 5 Pavia27100 Italy Sdu Robotics Maersk McKinney Moller Institute University of Southern Denmark Campusvej 55 Odense5230 Denmark

In industrial robotic contact-based operations it is necessary to have a detailed geometrical knowledge of the work-piece to automate the generation of the working trajectory. In many cases, the digital model is not available or it differs from its as built actual conditions. vision sensors, especially 3D vision sensors allows to scan the work-piece and reconstruct its digital copy that is used for the generation of the robotic working trajectory. In this paper we compare two algorithms for the generation of the 3D model of an unknown work-piece based on the use of the RGB-D images taken from different perspectives. the first technique, based on standard image reconstruction methods commonly used for reconstruction of indoor scenes where error in the order of few centimeters is negligible, is exploited in this work in order to be exploited in contact-based robotic operations where the geometrical error has to be limited to few millimeters. It is based on the analysis of the images to estimate the camera pose taking each image. Based on the pose, the algorithm integrates then the information contained in the images in a unique volume representing the scene. the second algorithm directly uses the known poses of the robot, stored while capturing each image, to integrate the information to create the model. the two algorithms are compared to evaluate the accuracy, acquisition time and elaboration time. the analysis is done considering two kinds of objects, the first one with regular shape, the second one corresponding to an actual industrial object. © 2022 the Authors. Published by ELSEVIER B.V.

关键词： Industrial robots

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Flame Recognition Algorithm for aerial cruising firefighting robot based on RGB and improved YOLOv5

Flame Recognition Algorithm for aerial cruising firefighting...

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computer vision, Image and Deep Learning (CVIDL), International conference on

作者： Jianan Fan Xin Zhan Department of Electronic Information Science and Technology Zhuhai College of Science and Technology Zhuhai China

With the development of automation, intelligence, and unmanned technology in the warehousing industry, aerial cruise fire robots will become safety protection equipment for large logistics centers, large ports and docks, and other public places. the visual recognition system of aerial cruise firefighting robots is crucial for the recognition performance of flames. During the process of robot cruising, lighting, sunlight, and reflective objects are the main obstacles that confuse flame recognition. this article uses the image preprocessing algorithm RGB to filter out the areas suspected of being in flames through RGB threshold. then, the filtered image is expanded and corroded through a filter, connecting the adjacent areas suspected of being in flames. Finally, the YOLOv5 algorithm model incorporating SE attention mechanism is used to perform flame recognition on the preprocessed image. this article uses the final algorithm model for experiments, and performs flame recognition on 5000 random photos, with a recognition accuracy of 96.291%.

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Object recognition on humanoids with poveated vision

Object recognition on humanoids with poveated vision

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IEEE-RAS International conference on Humanoid robots

作者： A. Ude G. Gheng Department of Automatics Joåâef Stefan Institute Ljubljana Slovenia Department of Humanoid Robotics and Computational Neuroscience ATR Computational Neuroscience Laboratories Kyoto Japan

Object recognition requires a robot to perform a number of nontrivial tasks such as finding objects of interest, directing its eyes towards the objects, pursuing them, and identifying the objects once they appear in the robot’s central vision. In this paper we describe a system that make use of foveated vision to solve the problem of object recognition on a humanoid robot. the system employs a biologically motivated object representation scheme based on Gabor kernel functions to represent multiple views of objects. We demonstrate how to utilize support vector machines to identify known objects in foveal images using this representation. A mechanism for visual search is integrated into the system to find a salient region and to place an object of interest in the field of view of foveal cameras. the framework also includes a control scheme for eye movements, which are directed using the results of attentive processing in peripheral images.

关键词： Object recognition robot vision systems Cameras Humanoid robots Eyes robotics and automation computer vision Lenses Face detection Layout

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Self-localization of Unmanned Aerial Vehicles Based on Optical Flow in Onboard Camera Images 4th

Self-localization of Unmanned Aerial Vehicles Based on Optic...

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4th International conference on Modelling and Simulation for Autonomous Systems (MESAS)

作者： Walter, Viktor Novak, Tomas Saska, Martin Czech Tech Univ Fac Elect Engn Dept Cybernet Multirobot Syst Karlovo Namesti 13 Prague 12135 2 Czech Republic

ISBN: (纸本)9783319760728;9783319760711

this paper proposes and evaluates the implementation of a self-localization system intended for use in Unmanned Aerial Vehicles (UAVs). Accurate localization is necessary for UAVs for efficient stabilization, navigation and collision avoidance. Conventionally, this requirement is fulfilled using external hardware infrastructure, such as Global Navigation Satellite System (GNSS) or camera-based motion capture system (VICON-like [37]). these approaches are, however, not applicable in environments where deployment of cumbersome motion capture equipment is not feasible, as well as in GNSS-denied environments. Systems based on Simultaneous Localization and Mapping (SLAM) require heavy and expensive onboard equipment and high amounts of data transmissions for sharing maps between UAVs. Availability of a system without these drawbacks is crucial for deployment of tight formations of multiple fully autonomous micro UAVs for both outdoor and indoor missions. the project was inspired by the often used sensor PX4FLOW Smart Camera [12]. the aim was to develop a similar sensor, but without the multiple drawbacks observed in its use, as well as to make the operation of it more transparent and to make it independent of a specific hardware. Our proposed solution requires only a lightweight camera and a single-point range sensor. It is based on optical flow estimation from consecutive images obtained from downward-facing camera, coupled with a specialized RANSAC-inspired post-processing method that takes into account flight dynamics. this filtering makes it more robust against imperfect lighting, homogenous ground patches, random close objects and spurious errors. these features make this approach suitable even for coordinated flights through demanding forest-like environment. the system is designed mainly for horizontal velocity estimation, but specialized modifications were also made for vertical speed and yaw rotation rate estimation. these methods were tested in a simulator and

关键词： UAV Localization Velocity sensors Rotation sensors Optical flow computer vision

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Autonomous robot control with DSP and video camera using MATLAB State-Flow chart

Autonomous robot control with DSP and video camera using MAT...

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European DSP Education and Research conference (EDERC)

作者： Aviv Lichtigstein Roy Or-El Arie Nakhmani Control and Robotics Laboratory Department of Electrical Engineering Technion-Israel Institute of Technology Israel

this paper presents an embedded system for autonomous control of irobot Create that consists of real time target tracking and robot navigation. Tracking and navigation algorithms were implemented using the TI DM6437 EVM board. the robot's performance demonstrates that a visual tracking and navigation can be efficiently and robustly implemented, and TI DSP is suitable for running both algorithms simultaneously due to its low power consumption and high-speed performance. the proposed tools have a steep learning curve, and they can be used as a platform for the further development.

关键词： computer languages Tracking Navigation robot vision systems MATLAB Instruments

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Robust Object Finding vision System based on Saliency Map Analysis

Robust Object Finding Vision System based on Saliency Map An...

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International conference on Awareness Science and Technology

作者： Jyun-han Wei Shih-Hung Wu Liang-Pu Chen Wen-Tai Hsieh Seng-cho T. Chou Dept. of CSIE Chaoyang University of Technology Taichung Taiwan (R.O.C) Institute for Information Industry Taipei Taiwan (R.O.C) Department of IM National Taiwan University Taipei Taiwan (R.O.C)

ISBN: (纸本)9781467321112

this paper describes a new method of constructing a saliency map that can be used in object finding for a robot vision system. A saliency map shows the weight of each pixel in an image. the weights represent the probability of the location of a given object. Traditionally, a saliency map is constructed based on the analysis of the image color features of the RGB color space. We redefine the saliency map of an image on the HSL color space, which makes our method more robust under a wide range of luminance. Experimental results show that the range can cover most cases in everyday life. thus, the system can successfully find objects under different conditions and various light sources.

关键词： robot vision saliency map object finding robot vision MAPPING(MAthEMATICAL) maps RGB colour space image analysis computer vision new methods LIGHT SOURCES FINDINGS Robustness

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Monocular-vision-based study on moving object detection and tracking

Monocular-vision-based study on moving object detection and ...

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International conference on New Trends in Information and Service Science, NISS

作者： Liu Dong Xi Lin College of Automatic Control Beijing Union University Beijing China Department of Computer Science and Technology Beijing University of Chemical and Technology Beijing China

ISBN: (纸本)9781424469826;9788988678183

In this paper, we present an approach for recognizing and tracking a moving color object which break into the robot's camera vision in the mobile robot. In order to obtain input feature for moving-object recognition, we perform image processing of the video sequence by background substraction method. Given the images of video sequence provided by a fixed camera on mobile robot, disparity images in different time are integrated into a tracking framework in order to find the HSV space based color features of the moving object. Based on the color object's moving and background substraction method, an color classifier based on the HS thresholds is trained to detect moving object. We show experimentally that the moving-object recognition performance can be improved significantly by using information about object's edge as an additional feature. through the recognition, we can find the center of the moving object and control the mobile robot's angle and rate to realize the vision-tracking of moving object. Our system aims at applications in the field of robot intelligence,where it is important to do run-on recognition in real-time, to allow for robot sel-learning and not to rely on appointed features.

关键词： Object detection Mobile robots robot vision systems Intelligent robots Cameras Video sequences Image recognition Image processing robot control Real time systems

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TER: A system for robotic Tele-echography 4th

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4th International conference on Medical Image Computing and computer-Assisted Intervention, MICCAI 2001

作者： Gonzales, Adriana Vilchis Cinquin, Philippe Troccaz, Jocelyne Guerraz, Agnès Hennion, Bernard Pellissier, Franck thorel, Pierre Courages, Fabien Gourdon, Alain Poisson, Gérard Vieyres, Pierre Caron, Pierre Mérigeaux, Olivier Urbain, Loïc Daimo, Cédric Lavallée, Stéphane Arbeille, Philippe Althuser, Marc Ayoubi, Jean-Marc Tondu, Bertrand Ippolito, Serge TIMC/IMAG lab Domaine de la Merci La Tronche cedexF-38706 France France Telecom R and D 28 chem du vieux Chêne BP 98 Meylan cedexF-38243 France Laboratoire Vision et Robotique 63 avenue de Lattre de Tassigny Bourges cedexF-18020 France SINTERS BP1311 Toulouse cedex 01F-31106 France PRAXIM Le Grand Sablon 4 av. de l’Obiou La TroncheF-38700 France CHU Trousseau Unité de Médecine et Physiologie Spatiale ToursF-37044 France CPDPN CHU de Grenoble BP 217 Grenoble cedex 9F-38043 France LESIA Electrical and CS Eng. Dept INSA Campus de Rangueil ToulouseF-31077 France

ISBN: (纸本)3540426973

the quality of ultrasound based diagnosis highly depends on the operator’s skills. Some healthcare centres may not have the required medical experts on hand when needed and therefore may not benefit from highly specialized ultrasound examinations. the aim of this project is to provide a reliable solution in order to perform expert ultrasound examinations in distant geographical areas and for the largest population possible. TER is a tele-robotic system designed and developed by a French consortium composed of universities, hospitals and industrial companies. One originality of TER is the development of a compliant slave robot actuated by muscles. this slave robot is teleoperated by an expert clinician who remotely performs the exam. In this paper, we present the architecture of TER and describe its components. © Springer-Verlag Berlin Heidelberg 2001.

关键词： Slave robots

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vision-Based Object Sorting in Dynamic Environments using YOLO for RoboCup ARM Challenge 2023 7

Vision-Based Object Sorting in Dynamic Environments using YO...

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7th IEEE conference on Information and Communication Technology, CICT 2023

作者： Sahu, Yash Kumar Mittal, Radhika Patel, Deep Maiti, Chayan Sreekumar, M. Indian Institute of Information Technology Design and Manufacturing Centre for AI IoT and Robotics Department of Mechanical Engineering Kancheepuram Chennai India Indian Institute of Information Technology Design and Manufacturing Centre for AI IoT and Robotics Department of Computer Science Kancheepuram Chennai India

ISBN: (纸本)9798350305173

In the intersection of Artificial Intelligence (AI) and robotics, autonomous object manipulation has emerged as a pivotal research domain, finding applications in sectors as diverse as manufacturing and healthcare. While significant strides have been made in object identification, trajectory planning, and manipulation tasks, these advancements often fall short in real-world, dynamic settings, revealing a critical research gap in algorithmic adaptability and computational efficiency. this paper addresses the gap by applying YOLOv4, a state-of-the-art object detection AI algorithm, within the context of the RoboCup Autonomous robot Manipulation (ARM) Challenge - a competitive platform designed to simulate real-world complexities in autonomous systems. the research objectives are twofold: firstly, the performance of YOLOv4 in object detection and classification under dynamically changing conditions is rigorously evaluated, employing varied training strategies in both simulated and real-world scenarios. Secondly, the robustness and adaptability of the algorithm in object manipulation tasks are scrutinized and facilitated by the real-world dynamics inherent to the competition. Empirical results demonstrate the algorithm's high accuracy, efficiency, and robustness in dynamic environments, substantiating its broader applicability in the development of autonomous systems. © 2023 IEEE.

关键词： Object detection

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