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15th IEEE International Conference on Industry Applications, INDUSCON 2023

作者： de Oliveira, Iure Rosa L. de Carvalho, Kevin B. Brandão, Alexandre S. Graduate Program in Computer Science Universidade Federal de Viçosa Viçosa Brazil Electrical Engineering Department Universidade Federal de Viçosa Viçosa Brazil

ISBN: (纸本)9798350314182

Multi-robot systems can provide substantial increase in efficiency and/or flexibility in different scenarios. Applications in various settings have been studied in the literature, such as disaster management, surveillance, object transportation as well as search-and-rescue. A particular case that can highly benefit from the employment of multiple agents is the logistics in a warehouse scenario. This work proposes an multi-agent Q-learning based algorithm with curriculum learning and transfer learning to perform the path planning process. With progressively more complex stages of training as well as knowledge transfer from one stage to another, the algorithm is capable of achieve high success rates. In order to validate the proposed method, simulations were done to compare it to other combinations of the used techniques, as well as using Q-learning only. Scalability tests were also performed. The proposed method achieved up to 94% success rate after training. © 2023 IEEE.

关键词： Curriculum Learning Mobile robotics Multi-Agent System Reinforcement Learning Transfer Learning

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Embracing Safe Contacts with Contact-aware Planning and Control

arXiv

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arXiv 2023年

作者： Li, Zhaoting Zamora, Miguel Zheng, Hehui Coros, Stelian Computational Robotics Lab Computer Science Department ETH Zurich Switzerland Soft Robotics Lab Department of Mechanical and Process Engineering ETH Zurich Switzerland

Unlike human beings that can employ the entire surface of their limbs as a means to establish contact with their environment, robots are typically programmed to interact with their environments via their end-effectors, in a collision-free fashion, to avoid damaging their environment. In a departure from such a traditional approach, this work presents a contact-aware controller for reference tracking that maintains interaction forces on the surface of the robot below a safety threshold in the presence of both rigid and soft contacts. Furthermore, we leveraged the proposed controller to extend the BiTRRT sample-based planning method to be contact-aware, using a simplified contact model. The effectiveness of our framework is demonstrated in hardware experiments using a Franka robot in a setup inspired by the Amazon stowing task. A demo video of our results can be seen here: https://***/2WeYytauhNg. © 2023, CC BY.

关键词： End effectors

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Integration of Convolutional Neural Networks for Real-Time Monitoring of Soil Health in Precision Agriculture 8

Integration of Convolutional Neural Networks for Real-Time M...

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8th International Conference on Electronics, Communication and Aerospace Technology, ICECA 2024

作者： Sunil, Tummapudi Pachiappan, Krishnagandhi Senthilrajan, S. Nagendar, Y. Maaliw, Renato R. Pavin, C. Malla Reddy Engineering College Malkajgiri Department of Cse Hyderabad India Nandha Engineering College Electrical and Electronics Engineering Tamil Nadu Erode India Rajalakshmi Engineering College Department of Robotics& Automation Tamil Nadu Chennai India Sr University Department of School of Computer Science and Artificial Intelligence Telangana Warangal India Southern Luzon State University Department of Cse Quezon Lucban Philippines Yar Tech Services Biomedical Engineer Hyderabad India

ISBN: (纸本)9798350367904

Convolutional Neural Networks (CNNs) represent a revolutionary breakthrough in improving crop productivity and sustainability when integrated into real-time monitoring systems for soil health in precision agriculture. CNNs are used in a novel way to analyze soil parameters directly from high-resolution photos taken by in-field sensors, such as moisture content, p H levels, and nutrient concentration. To forecast soil health measures, a CNN model was trained and validated using a collection of soil samples. The model achieved an accuracy rate of approximately 9 2 %. The CNN-based technique shortens the time needed for soil health evaluation by almost 80 % when compared to conventional approaches that involve manual sampling and laboratory analysis, allowing for quick corrective actions in the field. Additionally, more accurate and timely soil health monitoring was found to boost crop output prediction accuracy by 15 %. An up to 20 % decrease in the amount of resources used, especially water and fertilizers, can be achieved by using real-time data processing to make educated decisions about irrigation, fertilizing, and pest management. The CNN model offers scalability and adaptability across a range of crop varieties and soil conditions, and it can be easily integrated into current agricultural IoT frameworks. All things considered, using CNNs for soil health monitoring offers an economical and effective way to improve the accuracy and output of contemporary farming methods. © 2024 IEEE.

关键词： Convolutional neural networks

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On the Existence of Static Equilibria of a Cable-Suspended Load with Non-stopping Flying Carriers

On the Existence of Static Equilibria of a Cable-Suspended L...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Chiara Gabellieri Antonio Franchi Robotics and Mechatronics Department Electrical Engineering Mathematics and Computer Science (EEMCS) Faculty University of Twente Enschede AE The Netherlands Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy

ISBN: (数字)9798350357882

ISBN: (纸本)9798350357899

This work answers positively the question whether non-stop flights are possible for maintaining constant the pose of cable-suspended objects. Such a counterintuitive answer paves the way for a paradigm shift where energetically efficient fixed-wing flying carriers can replace the inefficient multirotor carriers that have been used so far in precise cooperative cable-suspended aerial manipulation. First, we show that one or two flying carriers alone cannot perform non-stop flights while maintaining a constant pose of the suspended object. Instead, we prove that three flying carriers can achieve this task provided that the orientation of the load at the equilibrium is such that the components of the cable forces that balance the external force (typically gravity) do not belong to the plane of the cable anchoring points on the load. Numerical tests are presented in support of the analytical results.

关键词： Task analysis Aircraft Gravity

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Self-Righting Shell for Robotic Hexapod

Self-Righting Shell for Robotic Hexapod

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IEEE International Conference on robotics and Automation (ICRA)

作者： Katelyn King Shai Revzen Department of Biomedical Engineering Robotics Institute University of Michigan Ann Arbor Department of Electrical Engineering and Computer Science Department of Ecology and Evolutionary Biology University of Michigan Ann Arbor

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Decimeter scale robots in human environments are small relative to obstacles they encounter, making them prone to flipping over and needing to self-right. We present a multifaceted shell that by its geometry alone enables the hexapedal robot MediumANT to passively self-right without the need for additional sensory feedback. We designed the shell by specifying the cross-sectional geometry in the yz and xy planes such that the robot returns to an upright position by rolling around the longitudinal (x) axis, and then tweaked the design to reduce the number of faces. We then attached the shell to the robot by modifying some of its chassis structural plates to extend to and support the shell. We evaluated the effectiveness of the shell in two experimental scenarios: passive righting – balancing the robot on each face of the shell before releasing the robot – and an intentional fall – walking the robot off a ledge at various approach angles. As intended by our design, the robot recovered the upright orientation from all starting faces in the passive righting test and righted itself and continued walking in all falling trials. This work presents an example of using biologically inspired simplicity to solve what would otherwise be a technically challenging problem.

关键词： Legged locomotion Geometry Structural plates Robot sensing systems Biology Faces

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Comparative Analysis among Categorical Shortest Path-finding Algorithms using OPSimDAZ

Comparative Analysis among Categorical Shortest Path-finding...

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International Conference on computer and Information Technology (ICCIT)

作者： Milton Bhowmick M. Akhtaruzzaman Department of Computer Science and Engineering Military Institute of Science and Technology (MIST) Dhaka Bangladesh Quantum Robotics and Automation Research Group (QRARG) Dhaka Bangladesh

ISBN: (数字)9798331519094

ISBN: (纸本)9798331519100

Efficient navigation of mobile robots is crucial for industrial applications. However, environmental obstacles can pose significant risks and hinder operational optimality. Thus, identifying the ideal algorithm through comparative analysis is imperative. This study examines five popular path planning algorithms; Dijkstra, BFS, A*, D* Lite, and Ant Colony Optimization (ACO); based on 2D grid simulation. The objective is to conduct performance analysis of these algorithms through a custom designed online simulation platform for visualization of path planning strategies. The methodology encompasses a thorough background study, environment setup, development of simulation platform, algorithm implementation, and result analysis with visualization. This study contributes by introducing a new simulation platform, and adding values to the existing knowledge of path planning analysis.

关键词： Visualization Ant colony optimization Navigation Heuristic algorithms Probabilistic logic Path planning Real-time systems Performance analysis Mobile robots Information technology

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Early Detection and Classification of Melanoma Based on Android MobileNet V2 Convolutional Neural Network

Early Detection and Classification of Melanoma Based on Andr...

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2023 International Seminar on Application for Technology of Information and Communication, iSemantic 2023

作者： Prabandari, Jasmine Iswarini Dyah Sari, Christy Atika Rachmawanto, Eko Hari Irawan, Candra Altamer, Bilal R. Alkhafaji, Mohamed Ayad University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia University of Dian Nuswantoro Study Program in Information Systems Semarang Indonesia Mosul University Presidency University of Mosul Mosul Iraq National University of Science and Technology Department of Computer Science DhiQar Iraq

ISBN: (纸本)9798350339215

Melanoma is a malignant form of cancer that affects the skin and has a particularly high mortality rate, so it requires early detection to increase the level of safety for users. Diagnosis and detection of skin cancer are usually done through manual screening and visual inspection. This process requires a long time, has high complexity, is subjective, and is prone to errors. CNN is one of the algorithms with advantages in accurate classification. In this research, early detection and classification of melanoma cancer were carried out based on two classes, namely benign and malignant using the Convolutional Neural Network method. Our proposed method yields an accuracy of 81.11% for the validation data. The accuracy results obtained can be improved by using more datasets and increasing the number of layers used. This study uses the CNN method using MobileNet V2 architecture to detect melanoma skin cancer. The class used is benign and malignant. © 2023 IEEE.

关键词： Convolutional neural networks

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DEEP LEARNING-BASED CHANNEL ESTIMATION FOR RIS-ASSISTED UAV-ENABLED WIRELESS COMMUNICATIONS SYSTEM

DEEP LEARNING-BASED CHANNEL ESTIMATION FOR RIS-ASSISTED UAV-...

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2023 International Conference on Innovation, Communication and engineering, ICICE 2023

作者： Tesfaw, Belayneh A. Lin, Hsin-Piao Tarekegn, Getaneh B. Juang, Rong-Terng Jeng, Shiann-Shiun Department of International Graduate Program in Electrical Engineering and Computer Science National Taipei University of Technology Taipei Taiwan Institute of Aerospace and System Engineering National Taipei University of Technology Taipei10608 Taiwan Department of Electrical and Computer Engineering National Yang-Ming Chiao Tung University Hsinchu30010 Taiwan Department of Electrical Engineering National Dong Hwa University Hualien Taiwan

ISBN: (纸本)9781839539954

Wireless communication via unmanned aerial vehicles (UAVs) has drawn a great deal of attention due to its flexibility in establishing line-of-sight (LoS) communications. However, in complex urban and dynamic environments, the movement of UAVs can be blocked by trees and high-rise buildings that obstruct directional paths. This problem can be effectively addressed by employing reconfigurable intelligent surfaces (RIS). To achieve this goal, accurate channel estimation in RIS-assisted UAV-enabled wireless communications is crucial. This paper proposes an accurate channel estimation model using long short-term memory (LSTM) for a multi-user RIS-assisted UAV-enabled wireless communications system. Simulation results showed that LSTM can effectively improve the channel estimation performance of RIS-assisted UAV-enabled wireless communications. © The Institution of engineering & Technology 2023.

关键词： Channel estimation

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Fabrication of Sensorsless Automated Guided Vehicle for Small Warehouse Rack Management

Fabrication of Sensorsless Automated Guided Vehicle for Smal...

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2025 IEEE International Conference on Computational, Communication and Information Technology, ICCCIT 2025

作者： Sahu, Neelesh Kumar Chaturvedi, Piyush Gupta, Vaishali Patel, Ruchi Verma, Ashok Shrivastava, Megha Gyan Ganga Institute of Technology and Sciences Artificial Intelligence and Robotics MP Jabalpur India IPS Academy Institute of Engineering & Science Department of Computer Sc. & Engg. MP Indore India Gyan Ganga Institute of Technology and Sciences MP Jabalpur India Medicaps University Department of Mathematics MP Indore India

ISBN: (纸本)9798331512965

Automated guided vehicles (AGVs) are an essential part of today's logistics networks because they save time, reduce wear and maintenance expenses, and maximize efficiency in route *** creation of AGVthat is capable of effectively managing warehouse racks without the utilization of sensors is the primary emphasis of this project. In order to travel and carry out duties, the AGVruns on predetermined pathways and makes use of a button-based interface. For the purpose of offering an efficient and costeffective solution for the automation of small warehouses, it is outfitted with a lever mechanism that is operated by a servo motor and features the ability to connect and move racks. © 2025 IEEE.

关键词： Automatic guided vehicles

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Maintaining Visibility of Dynamic Objects in Cluttered Environments Using Mobile Manipulators and Vector Field Inequalities

Maintaining Visibility of Dynamic Objects in Cluttered Envir...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Fatih Dursun Bruno Vilhena Adorno Simon Watson Wei Pan Department of Electrical and Electronic Engineering Manchester Centre for Robotics and AI University of Manchester UK Department of Computer Science

Vision-based perception has become prevalent in robotic applications, especially in those where the control loop relies on visual data, such as visual servoing. For those applications, ensuring that the features or target object remain visible to the camera is critical, necessitating visibility-aware control. In this paper, we propose a method to guarantee the visibility of a dynamic object using a constrained kinematic controller and Vector Field Inequalities (VFIs) to include a linear visibility constraint. Unlike existing methods, we introduce constraints into the kinematic controller to ensure the target's visibility without needing a trajectory optimizer or local planner. Our method maintains the target object in the camera field of view (FoV) by representing the FoV with four infinite planes and maintaining the distance between the target object and each plane higher than a predefined distance. We evaluated the proposed approach using a mobile manipulator in two simulations involving cluttered environments: the first scenario involves a stationary target object, whereas the second scenario presents a more challenging workspace involving a moving target. Our results demonstrate that the proposed approach successfully maintains the target within the FoV while avoiding obstacles in the workspace, showing the potential of our method to improve the safety and reliability of visual-servoing-based robotic systems.

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