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14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Bhargava, Ankur Singholi, Ajay S. Suhaib, Mohd. Jamia Millia Islamia Faculty of Engineering and Technology Delhi India University School of Robotics & Automation Robotics & Automation Delhi India

ISBN: (纸本)9798350335095

Automated guided vehicles (AGVs) have emerged as crucial equipment in sectors that demand reliable and effective transportation and material handling systems. The design and control features of AGV systems are discussed in general terms in this study, with an emphasis on important factors and recent developments. The vehicle platform, sensing and perception systems, navigational algorithms, and control architecture are all essential parts of the design of an AGV system. To fit the application's unique requirements, the vehicle platform must be properly developed, taking into account elements like load capacity, maneuverability, and power supply. The AGV can sense its surroundings and maneuver on its own thanks to the choice and integration of sensors including LiDAR, cameras, and encoders. Simultaneous Localization and Mapping (SLAM), one of the most sophisticated perception algorithms, is essential for precisely mapping the environment and locating the AGV within it. Because of navigation algorithms, AGVs can efficiently plan their routes, avoid dangers, and reach their targets. Methods for establishing a path enable smooth, collision-free travel by accounting for factors including distance, time, and dynamic restrictions. Real-time control systems regulate the AGV's speed, acceleration, and steering, enabling accurate and secure operation in a variety of situations. The controls design should enable monitoring of the system and detection of problems in along with enabling integration of perception, navigating, and control modules. This paper examines the mechanical and electrical design of a test prototype autonomous guided vehicle (AGV). The SLAM technique apply in the present work successfully resolves the localization problem in conjunction with the navigation algorithm. © 2023 IEEE.

关键词： Electric loads

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Enhanced Surveillance Abilities Through Object Detection in Autonomous Robots

Enhanced Surveillance Abilities Through Object Detection in ...

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2024 International Conference on System, Computation, automation and Networking, ICSCAN 2024

作者： Pesha, J.V. Jotham, Golvainbec Thirumalai, C.K. Nithish Kumar, V. Sasirekha, M. Manakula Vinayagar Institute of Technology Dept. of Robotics and Automation Puducherry605107 India

ISBN: (纸本)9798331510022

The system emphasizes the operation of an autonomous environment monitoring robot with the capability of object detection and tracking using OpenCV and mobile application, we gather real-time video data from the environment with the help of an ESP-32 cam module and cast the data to the respective mobile application forum for the visualization and analysis of the surrounding space with the help of WIFI (wireless fidelity). We use an ESP-32 camera-based autonomous surveillance robot integrated with a camera and ESP-32 microcontroller for real-time object detection using OpenCV with the help of pretrained models like mobile net, tensor flow, etc. The ESP-32 cam module processes images controls motors for movement and communicates wirelessly for security applications offering a versatile solution for tracking and monitoring operations. © 2024 IEEE.

关键词： Cams

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Design and Development of a Visual - SLAM based Automated Guided Vehicle 5

Design and Development of a Visual - SLAM based Automated Gu...

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5th IEEE International Conference on Advances in Electronics, Computers and Communications, ICAECC 2023

作者： Bhargava, Ankur Singholi, Ajay S. Suhaib, Mohd. Faculty of Engineering and Technology Jamia Millia Islamia Delhi India University School of Robotics & Automation India Robotics & Automation Delhi India

ISBN: (纸本)9798350305449

The automobile industry is currently undergoing fast change as big manufacturers devote their attention to the development of future self- driving vehicles or automated guided vehicles. As a result, mobile robots and current automotive technologies are integrating to create the area of autonomous navigation. The camera sensor is the one garnering the most attention in terms of autonomy sensor research due to the large amount of information it provides for object detection and classification algorithms in addition to depth, coloring, size, and texture recognition. In the last ten years, there have been significant advancements in computing capabilities and image analysis algorithms. The requirement for developing low-level motion controllers grew as a consequence of the increase in machine vision performance and capabilities. This article discusses mecanum wheel mobile robotic applications of vision and SLAM-based motion controller. When using sensors like cameras or Lidar, autonomous mobile robots usually use the vision- based & simultaneous localization and mapping (SLAM) technology. The four-wheeled autonomous robot model that was utilized in the studywas created using a Jetson board with high performance processor, a depth camera, and LIDAR sensors along with ROS's RVIZ software. © 2023 IEEE.

关键词： Mobile robots

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Trash Detection in Water Bodies Using Yolo With Explainable AI Insight 6

Trash Detection in Water Bodies Using Yolo With Explainable ...

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6th International Conference on robotics and automation in Industry, ICRAI 2024

作者： Rasheed, Shafaq Mirza, Amal Saeed, Muhammad Saad Yousaf, Muhammad Haroon University of Engineering and Technology Department of Computer Engineering Taxila Pakistan National Center of Robotics and Automation Swarm Robotics Lab Taxila Pakistan

ISBN: (纸本)9798350355703

Waste disposal into water bodies is a serious concern for environmental engineers, often resulting in urban flooding, soil degradation in agricultural areas, and freshwater pollution. Additionally, trash accumulation in water bodies threatens ma-rine life by introducing contaminants through storm drains, rivers, and other channels. Furthermore, the unique character-istics of underwater environments, including high noise levels, low visibility, and color variation, pose challenges for trash detection. Thus, addressing this issue is crucial for environmental sustainability. The work focuses on both floating and submerged trash in water bodies. Typically, the detection of trash on water bodies is impacted by environmental variability, diverse appearance, and background clutter. These conditions also make usual object detection techniques less effective. Deep learning methods have shown promise in handling challenging visual tasks, therefore researchers have turned to them to get over these challenges. In this work, we focus on applying different versions of YOLO to the problem of water trash detection. To assess these models' performance, we use four different datasets: Trash Flow rate Dataset, DeepTrash, FloW, and TrashICRA. Each dataset represents various trash types under different conditions such as underwater trash and floating trash. Our study attempts to identify the best method suitable for the detection of aquatic waste. Our results highlight the effectiveness of YOLO variants in identifying the presence of trash in water ecosystems. By leveraging Grad-CAM we gain insights into the interpretability and transparency of deep learning models thus enabling Explainable AI. This approach will also contribute to the understanding and trustworthiness of artificial systems deployed for trash detection applications by providing a transparent view of decision making process of deep learning models. © 2024 IEEE.

关键词： Storm sewers

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Robotic Sensorized Gastroendoscopy with Wireless Single-Hand Control

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Current Directions in Biomedical Engineering 2022年第1期8卷 66-69页

作者： García, Gabriela Fischer, Nikola Marzi, Christian Mathis-Ullrich, Franziska Health Robotics and Automation Laboratory Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Karlsruhe 76131 Germany

The manipulation of flexible endoscopes is a procedure that requires great dexterity since it requires the synchronization and use of both hands in parallel. Imprecise handling during gastroendoscopy could harm the digestive tract. Our solution allows the physician to use only one hand to wirelessly control the forward, backward, and tip bending motion. The proposed system provides endoscopic vision and tactile impact force sensing at the tip to detect the force applied to tissue and thus avoid damage. We experimentally evaluate the handling of the robotic system in open space and inside a medical phantom. The results revealed a training effect with less time demand for task completion and reduction of average impact force after only 5 runs. The proposed system was successfully controlled using one hand and, together with the force information, could enhance the physician's experience during endoscopy. Future work will address axial control and an intensive user study with clinical experts. © 2022 by Walter de Gruyter Berlin/Boston.

关键词： robotics

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Effect of Tine Shaped Furrow Opener on Dry Soil Using Discrete Element Modelling

Effect of Tine Shaped Furrow Opener on Dry Soil Using Discre...

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2023 International Conference on robotics and automation in Industry, ICRAI 2023

作者： Mohiz, Abdul Nasir, Fazal E. Shah, Kamran University of Engineering & Technology Department of Mechatronics Engineering Peshawar Pakistan Advanced Robotics & Automation Lab National Center of Robotics & Automation Peshawar Pakistan

ISBN: (纸本)9781665464727

Tillage of the soil is the most important consideration when it comes to the implementation of agricultural practices. Increases in crop yield has been achieved through a variety of agricultural practices thanks to the discoveries of various agricultural experts. The planting process is the one that has the greatest impact on the crop's overall health. The hull can be more precisely prepared for the seed-planting trench with the assistance of furrows. A variety of furrow openers are currently undergoing the implantation process. Studying dynamic systems that are discontinuous in nature can be done with the help of discrete element modelling. The simulation of a tine-shaped furrow opener using the EDEM package software was carried out for three different speeds. When the speed of an object increases, so does the force it exerts on it. Additionally, the length of an object has an effect on the force it exerts. Additionally, taken into consideration were the profiles that were generated in the soil. To carry out statistical validation of the results analysis of variation (ANOVA) was done. The results provided a basis for calculating a confidence level of 95%. For the furrow openers, it was suggested that a speed of 0.495 meters per second, which is equivalent to 1.76 kilometers per hour, be used. © 2023 IEEE.

关键词： Tillage

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PCE: Multi-Agent Path Finding via Priority-Aware Communication & Experience Learning

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-13页

作者： Gao, Jianqi Li, Yanjie Ye, Zhaohui Wu, Xinyu Department of Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics and School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China

Multi-agent path finding (MAPF) is an essential issue for warehouse automation, where multiple agents plan collision-free paths from the start to goal positions. Reinforcement learning (RL) has been employed to develop partially observable distributed MAPF methods that can be scaled to any number of agents. However, existing RL-based MAPF methods still have some limitations in handling redundant information and avoiding deadlock, resulting in a low success rate or longer makespan. This paper proposes a Priority-aware Communication & Experience learning method (PCE), which combines RL with a novel priority-aware multi-agent communication and a new priority-aware deadlock experience replay to tackle this challenge. To be specific, our innovation encompasses two-fold. Our proposed communication mechanism aims to handle redundant information, which establishes a dynamic communication topology based on agents' priorities and proposes a two-head priority-aware graph attention network to aggregate information. In order to help the agent avoid deadlock, we prioritize the expert experience that solves the deadlock when performing experience replay. We conduct multiple simulation experiments on warehouse-like structured grid maps. Compared with the state-of-the-art RL-based MAPF methods, PCE performs significantly better with a higher success rate and lower makespan in small and large MAPF and higher average throughput in the lifelong MAPF, which can further improve the efficiency of warehouse automation. Finally, we validate PCE using three Turtlebot3-Burger robots, which shows that PCE can be applied in real warehouse automation scenarios. IEEE

关键词： Aggregates

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Gaze Betray You: Abnormal Attention Detection from Human-Robot Interaction Dynamics

Gaze Betray You: Abnormal Attention Detection from Human-Rob...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Mu, Fengjun Zhang, Jingting Zou, Chaobin Huang, Zonghai Huang, Rui Cheng, Hong School of Automation Engineering University of Electronic Science and Technology of China Center for Robotics Chengdu China

ISBN: (纸本)9781665481090

Monitoring abnormal attention has a wide range of applications in Human-Robot Interaction systems, such as autonomous driving, virtual reality, and remote operation. Due to factors like fatigue, drowsiness, and distraction, human attention can deviate from tasks that require focus, resulting in abnormal attention during interactions. Monitoring for abnormal attention is essential to ensure the safety of human-robot interactions. However, existing methods often rely on un-explainable algorithms such as neural networks, making them difficult to trust in scenarios like autonomous driving, where explicit decision-making processes and mechanisms are required. This paper presents EyeAAD, an abnormal attention detection method based on dynamic system theory. This method uses gaze signals from a serious game designed to simulate human-robot interaction. We developed several attention-related features for interpretable modeling using a deterministic learning method. By analyzing the matching relationship between the gaze signal and the predicted status from the learned dynamic models, we can detect abnormal human attention patterns. To validate our approach, we designed a serious game for eye movement data acquisition in human-robot interaction. Our analysis showed that EyeAAD enables efficient, real-time monitoring of human attention. © 2024 IEEE.

关键词： Serious games

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Speed and Distance Detection for Highway Traffic using Python

Speed and Distance Detection for Highway Traffic using Pytho...

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2023 International Conference on System, Computation, automation and Networking, ICSCAN 2023

作者： Devi, G Renuka Athiyan, S. Thamizh, K. Ilan Varthini, V. Hema Manakula Vinayagar Institute of Technology Department of Robotics and Automation Puducherry India

ISBN: (纸本)9798350315127

This Python -based scheme presents an innovative approach to bolstering road safety by harnessing the power of computer vision and machine learning. The primary objective is to provide drivers with crucial real-time information for informed lane change decisions, thereby reducing the risk of accidents. The system integrates advanced techniques such as object detection, tracking algorithms, and depth estimation to analyze video feeds from highway cameras. The system's core functionality involves estimating the speed and distance of vehicles on the highway. Object detection algorithms, including YOLO, SSD, and Faster R-CNN, are employed to identify and track vehicles in the video feed. Depth estimation techniques enhance accuracy by determining relative distances between vehicles. Machine learning algorithms, such as recurrent neural networks (RNNs) and long short-term memory networks (LSTMs), predict future positions and speeds, enabling the system to identify potential conflicts. © 2023 IEEE.

关键词： Python

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Robot Vacuum Cleaner Using SLAM and ROS

Robot Vacuum Cleaner Using SLAM and ROS

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2024 International Conference on Knowledge Engineering and Communication Systems, ICKECS 2024

作者： Arjun, M. Oliver, Cliff Andrew Joseph, Anju Mary Adi Shanakara Institute of Engineering and Technology Dept. of Robotics and Automation Ernakulam Kalady India

ISBN: (纸本)9798350359688

For the past few years, robot vacuum cleaners have made a huge impact on society. There are different types of robot vacuum cleaners, differentiated based on their method of operation. In this paper, we present a comprehensive framework for enhancing the autonomous capabilities of robot vacuum cleaners by integrating the Robot Operating System (ROS) and Simultaneous Localization and Mapping (SLAM) techniques. Our robot uses laser mapping to map the entire environment and is faster than other robot vacuum cleaners. Our approach not only enhances the performance of robot vacuum cleaners but also provides a foundation for future research and development in the field of domestic service robots. The ROS and SLAM integration framework presented in this paper can be extended to other robotic applications, advancing the state of the art in autonomous navigation and perception for household robotics. © 2024 IEEE.

关键词： SLAM robotics

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