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23rd International Conference on Control, Automation and Systems, ICCAS 2023

作者： Ono, Seiya Kim, Hyun-Woo Cho, Myungjin Lee, Min-Chul Kyushu Institute of Technology Department of Computer Science and Networks Fukuoka Iizuka820-8502 Japan School of ICT Robotics and Mechanical Engineering Iitc Hankyong National University Kyonggi-do Anseong17579 Korea Republic of

ISBN: (纸本)9788993215274

In this paper, we propose a system that enables visualization under the situation of scattering media such as fog and smoke by Peplography which is scattering media removal system, on a small GPU machine. Compared to conventional haze removal techniques, peplography technology is capable of removing more dense scattering media and can handle cases where the density of fog varies in the image. On the other hand, the conventional peplography process is performed on a desktop PC, and no system has yet been developed to perform peplography in an outside environment. Thus, we have developed a peplography system using the Jetson AGX Xavier, a single-board computer equipped with a GPU, which is superior to conventional methods in terms of portability, execution speed, and power consumption. We also demonstrate the performance of this system by conducting experiments using this system under a simulated scattering media scene and evaluating the obtained results in terms of FPS and the image evaluation metric. © 2023 ICROS.

关键词： Graphics processing unit

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A Real-Time DETR Approach to Bangladesh Road Object Detection for Autonomous Vehicles

arXiv

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arXiv 2024年

作者： Shahan, Irfan Nafiz Hossain, Arban Sakib, Saadman Nabil, Al-Mubin Department of Electrical and Electronic Engineering Shahjalal University of Science and Technology Sylhet Bangladesh Department of Robotics and Mechatronics Engineering Dhaka University Dhaka Bangladesh Department of Computer Science and Engineering Shahjalal University of Science and Technology Sylhet Bangladesh

In the recent years, we have witnessed a paradigm shift in the field of computer Vision, with the forthcoming of the transformer architecture. Detection Transformers has become a state of the art solution to object detection and is a potential candidate for Road Object Detection in Autonomous Vehicles. Despite the abundance of object detection schemes, real-time DETR models are shown to perform significantly better on inference times, with minimal loss of accuracy and performance. In our work, we used Real-Time DETR (RTDETR) object detection on the BadODD Road Object Detection dataset based in Bangladesh, and performed necessary experimentation and testing. Our results gave a mAP50 score of 0.41518 in the public 60% test set, and 0.28194 in the private 40% test set. © 2024, CC BY-NC-SA.

关键词： Object detection

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ASFM: Augmented Social Force Model for Legged Robot Social Navigation 23

ASFM: Augmented Social Force Model for Legged Robot Social N...

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23rd IEEE-RAS International Conference on Humanoid Robots, Humanoids 2024

作者： Ægidius, Sebastian Chacón-Quesada, Rodrigo Delfaki, Andromachi Maria Kanoulas, Dimitrios Demiris, Yiannis Imperial College London Personal Robotics Lab Department of Electrical and Electronic Engineering LondonSW7 2AZ United Kingdom University College London Robot Perception and Learning Lab Department of Computer Science Gower Street LondonWC1E 6BT United Kingdom Ai Centre Department of Computer Science Ucl United Kingdom Archimedes/Athena Rc Greece

ISBN: (纸本)9798350373578

Social navigation in robotics primarily involves guiding mobile robots through human-populated areas, with pedestrian comfort balanced with efficient path-finding. Although progress has been seen in this field, a solution for the seamless integration of robots into pedestrian settings remains elusive. In this paper, a social force model for legged robots is developed, utilizing visual perception for human localization. In particular, an augmented social force model is introduced, incorporating refined interpretations of repulsive forces and avoidance behaviors based on pedestrian actions, alongside a target following mechanism. Experimental evaluation on a quadruped robot, through various scenarios, including interactions with oncoming pedestrians, crowds, and obstructed paths, demonstrates that the proposed augmented model significantly improves upon previous baseline methods in terms of chosen path length, average velocity, and time-to-goal for effective and efficient social navigation. The code isopen-source, while video demonstrations can be found on the project's webpage: https://***/ASFM/ © 2024 IEEE.

关键词： Mobile robots

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Explorative Study on Motor Interference During Synchronous Human and Robot Arm Movements Under Varied Presence of a Robot Head

Explorative Study on Motor Interference During Synchronous H...

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IEEE International Conference on robotics and Biomimetics

作者： Mertcan Kaya Kolja Kühnlenz Robotics Research Lab Department of Electrical Engineering and Computer Science Coburg University of Applied Sciences and Arts Coburg Germany

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

This paper investigates the influence of a static robot head on deviations of human hand movements from task direction (motor interference) during simultaneous human and robot arm movements using a collaborative robot arm. Synchronous vertical and horizontal human and robot arm movements are conducted in all combinations (within-subjects factors direction and congruency). The presence of the head (head/ no head) is varied as a between-subjects factor. In this first step, only its motionless presence is deliberately focused at, in order to exclude contributions by eye- or head-movement behavior or facial expressions being difficult variables to generalize from. Participants' hands are tracked optically marker-based and deviations from task-related vertical, respectively, horizontal movements are evaluated. In contrast to expectations, results do not show a significant impact of the robot head on motor interference. Thus, there is evidence, that appearance might not be an activating factor for motor interference in HRI.

关键词： Hands Tracking Neurons Humanoid robots Morphology Interference Motors Manipulators Mirrors Robots

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Analysis of Accurate Focal Points and Automatic Method of Digital Holographic Microscopy (DHM) for Obtaining an Accurate 3D Profile 23

Analysis of Accurate Focal Points and Automatic Method of Di...

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23rd International Conference on Control, Automation and Systems, ICCAS 2023

作者： Ono, Taishi Kim, Hyun-Woo Cho, Myungjin Lee, Min-Chul Kyushu Institute of Technology Department of Computer Science and Networks Fukuoka Iizuka820-8502 Japan School of ICT Robotics and Mechanical Engineering Iitc Hankyong National University Kyonggi-do Anseong17579 Korea Republic of

ISBN: (纸本)9788993215274

Currently, Digital Holographic Microscopy(DHM) is used for researching disease diagnosis or microbes. It cannot obtain the correct three-dimensional (3D) profile for a little noise because biological cells are microscopic. Then we need images of the focal point of DHM for reducing noise. However, in DHM, the depth of field becomes smaller influenced by the objective lens. In addition, focusing to obtain hologram images of biological cells in conventional DHM systems is entirely manual, because the decision of the focal point is made by the photographer's senses, which makes it even more difficult to focus on the object. These factors make it difficult for the conventional DHM system to acquire images of the focal points. Therefore, in this paper, we propose the analysis of accurate focusing points using a noise map. This eliminates the illusion or misperception that is a drawback of the manual. We improved an accurate 3D profile. 3D profiles were created at the focal point by the proposed method and at the positions before and after the focal points, and evaluated for SNR. From this, the proposed method can be used to analyze biological cells and microstructures. © 2023 ICROS.

关键词： Holograms

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Implementation of Various Neural-Network-Based Adaptive Speed PI Controllers for Dual-Three-Phase PMSM 48

Implementation of Various Neural-Network-Based Adaptive Spee...

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48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

作者： Yin, Zhenxiao Zhao, Hang Robotics and Autonomous Systems Thrust Guangzhou China The Hong Kong University of Science and Technology Department of Electronic & Computer Engineering Hong Kong Hong Kong

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

This paper provides a preliminary study on applying Neural Network (NN) based proportional and integral (PI) controllers with the positional PI principle. This method is set into the speed loop of a dual-three-phase permanent magnet synchronous motor (PMSM), where the vector space decomposition method (VSD) is utilized. The proposed methods are single-layer neural network (SNN), backpropagation neural network (BPNN), and radial basis function neural network (RBFNN). These methods aim to reduce the overshoot of the speed tracking in control problems. By optimizing the current reference output, the copper loss can also be reduced at the same time. Finally, the control performances using traditional PI, SNN-based PI, BPNN-based PI, and RBFNN-based PI are compared by adopting a self-defined scorecard with different evaluation indices. © 2022 IEEE.

关键词： Vector spaces

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Improving sharpness-aware minimization by lookahead 24

Improving sharpness-aware minimization by lookahead

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Proceedings of the 41st International Conference on Machine Learning

作者： Runsheng Yu Youzhi Zhang James T. Kwok Department of Computer Science and Engineering The Hong Kong University of Science and Technology Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science & Innovation CAS

Sharpness-Aware Minimization (SAM), which performs gradient descent on adversarially perturbed weights, can improve generalization by identifying flatter minima. However, recent studies have shown that SAM may suffer from convergence instability and oscillate around saddle points, resulting in slow convergence and inferior performance. To address this problem, we propose the use of a lookahead mechanism to gather more information about the landscape by looking further ahead, and thus find a better trajectory to converge. By examining the nature of SAM, we simplify the extrapolation procedure, resulting in a more efficient algorithm. Theoretical results show that the proposed method converges to a stationary point and is less prone to saddle points. Experiments on standard benchmark datasets also verify that the proposed method outperforms the SOTAs, and converge more effectively to flat minima.

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Design and Implementation of an On-Board System for a Spider Robot 1st

Design and Implementation of an On-Board System for a Spider...

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1st International Conference on Computing and Emerging Technologies, ICCET 2023

作者： Nauman, Nasir Mustafa, Hirra Ashraf, Abrar Khalil, Hisham Department of Computer Science Superior University Lahore Pakistan Department of Computer Science Sharif College of Engineering and Technology Lahore Lahore Pakistan Embedded System and Robotics Lab Department of Technology The University of Lahore Lahore Pakistan

ISBN: (纸本)9783031776199

This paper presents the design of a system onboard spider robot for rescue services. The spider has the six-leg walking pattern that contains the total number of 18 servo motors. In order to reduce the payload, the abdomen of the spider is made with RF4 printed circuit board (PCB). Whereas, the abdomen is also used as the main structure of the robot to attach the rest of the system. Wherein, two pulse-width modulations (PWM) module are controlled by Arduino Nano, the Bluetooth module is used for communication link and bulk converter for the power supply. The spider robot is operated with an in-house developed Android application. It has been observed that the spider robot has a stable walking response along with the multiple excise performance. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Machine design

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Lighting the Smart Way: A Technological Odyssey in Urban Street Illumination

Lighting the Smart Way: A Technological Odyssey in Urban Str...

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International Conference on Advanced Computing and Communication Systems (ICACCS)

作者： M S Vinu P Kanaga Priya P Thilakaveni J M Ashforn Hermina K Prashanthini M Misba Department of Computer Science and Engineering Nehru Institute of Engineering and Technology Coimbatore India Department of Computer Science and Engineering KPR Institute of Engineering and Technology Coimbatore India Department of Computer Engineering PSG Polytechnic College Coimbatore India Department of Artificial Intelligence and Data Science Bannari Amman Institute of Technology Erode India Department of Robotics and Automation Sri Ramakrishna Engineering College Coimbatore India Department of Computer Science and Engineering Bethlahem Institute of Engineering Karungal Nagercoil India

ISBN: (数字)9798350384369

ISBN: (纸本)9798350384376

The development of intelligent street light systems has ushered in a new era of efficiency and sustainability in urban infrastructure. The proposed work studies the integration of modern sensors and Internet of Things (IoT) technologies to increase the functionality of street lights. The major components include Light Dependent Resistors (LDR) for automatic light management, an MQ135 sensor for air quality monitoring, and a fog detection system employing a laser module and LDR. These sensors are integrated with the ESP8266, providing cloud integration for real-time data visualization and monitoring. Additionally, solar panels are employed to enhance energy efficiency. The proposed methodology digs into the precise implementation, data analysis, and the potential of this system to alter urban lighting infrastructure

关键词： Smart cities Lighting Data visualization Collaboration Sensor systems Real-time systems Energy efficiency Internet of Things Sustainable development Intelligent sensors

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Crop and Weeds Classification in Aerial Imagery of Sesame Crop Fields Using a Patch-Based Deep Learning Model-Ensembling Method 2

Crop and Weeds Classification in Aerial Imagery of Sesame Cr...

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2nd International Conference on Digital Futures and Transformative Technologies, ICoDT2 2022

作者： Moazzam, S. Imran Khan, Umar S. Nawaz, Tahir Qureshi, Waqar S. National University of Sciences and Technology National Centre of Robotics and Automation Department of Mechatronics Engineering Islamabad Pakistan Technological University Dublin Department of Computer Science Dublin Ireland

ISBN: (纸本)9781665498197

Sesame (Sesamum indicum L.) is an important commercial and food crop, and its yields is limited by many insects, pests, diseases, and weeds. Autonomous aerial agrochemicals spray application on sesame fields using a drone aims to save crop from these yield limiting factors and in addition agrochemicals application quantity and site could be controlled, and human health is expected to be protected. For accurate and selective spray application, autonomous systems would need some parameters to distinguish between crop, weed and background. In this research an aerial sesame field dataset has been collected with the focus to classify patch areas of sesame and weeds present in the field. Dataset was captured using Agrocam. We have developed a patch image-based classification approach along with a novel SesameWeedNet convolutional neural network (CNN) inspired by the layer's configuration of VGG networks and depth-wise convolutions of the MobileNet. The small model contains 6 convolutional layers, and it runs faster and accurately on small patch images. Our approach breaks 1920×1080-pixel images into smaller patch images of size 45×45 pixels. After that, these small patch images are fed to a relatively small CNN for training, validation, and finally for classification. Patch based model ensemble and dataset grouping are two major parts in our methodology. Our system recommends the dataset grouping according to vegetation present in the images to enhance classification results. We have achieved accuracy up to 96.7% with our proposed method. We have tested our system under sunlight variation, in wet and dry soil conditions and at different growth stages. To the best of our knowledge, no attempt has been made to classify and treat crop and weeds in sesame fields at the post-emergence stage previously. In this research we have made the contribution of aerial sesame-weed dataset and a complete deep learning-based approach to classify weeds in sesame fields under variable lighti

关键词： Crops

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