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QUB-PHEO: A Visual-Based Dyadic Multi-View Dataset for Intention Inference in Collaborative Assembly

IEEE ACCESS 2024年 12卷 157050-157066页

作者： Adebayo, Samuel Mcloone, Sean Dessing, Joost C. Queens Univ Belfast Ctr Intelligent Autonomous Mfg Syst Belfast BT7 1NN North Ireland Queens Univ Belfast Sch Elect Elect Engn & Comp Sci Belfast BT7 1NN North Ireland Queens Univ Belfast Sch Psychol Belfast BT7 1NN North Ireland

QUB-PHEO introduces a visual-based, dyadic dataset with the potential of advancing human-robot interaction (HRI) research in assembly operations and intention inference. This dataset captures rich multimodal interactions between two participants, one acting as a 'robot surrogate,' across a variety of assembly tasks that are further broken down into 36 distinct subtasks. With rich visual annotations-facial landmarks, gaze, hand movements, object localization, and more-for 70 participants, QUB-PHEO offers two versions: full video data for 50 participants and visual cues for all 70. Designed to improve machine learning models for HRI, QUB-PHEO enables deeper analysis of subtle interaction cues and intentions, promising contributions to the field.

关键词： Human-robot interaction robots Assembly Visualization Complexity theory Encoding Collaboration Annotations Service robots Inference algorithms computer vision dyadic interaction multi-cue dataset multi-view dataset computer vision task-oriented interaction

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Absolute Pose Estimation for a Millimeter-Scale vision System

Absolute Pose Estimation for a Millimeter-Scale Vision Syste...

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2024 International Conference on intelligent robots and Systems

作者： Ozturk, Derin Wang, Zilin Helbling, E. Farrell Cornell Univ Sch Elect & Comp Engn Ithaca NY 14850 USA

ISBN: (纸本)9798350377712;9798350377705

vision is an important component of robotic perception systems due to the rich information provided by high resolution image sensors, but computer vision algorithms can be computationally expensive and ill-suited to resource-constrained robotic systems. Here, we present a mm-scale vision system capable of performing absolute pose estimation at 16.5 FPS. This novel vision system uses a commercial-off-the-shelf sensor and microcontroller unit, as well as planar light-based landmarks in the environment to simplify feature detection. We exploit the structure of the planar pose problem to reduce algorithmic complexity and improve latency and energy consumption through software-, processor-, and hardware-in-the-loop testing. The end-to-end system consumes 49 mA of current and computes absolute pose estimates within 15 mm over a number of reference trajectories.

关键词： Machine vision

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intelligent communication of two humanoid robots based on computer vison

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MULTIMEDIA TOOLS AND APPLICATIONS 2024年第23期83卷 63459-63477页

作者： Juang, Li-Hong Nanjing Univ Informat Sci & Technol Sch Artificial Intelligence Sch Future Technol Nanjing 210044 Peoples R China

The focus of this paper is on investigating the use of visual communication between two humanoid robots, in order to enhance the coordination of tasks between them. The problem continues to be an interesting and fruitful area of research from the days of using multiple robot manipulator arms for manufacturing as well as space robotics to current research in medical robotics. The approach here is to employ several off-the-shelf algorithms, software and hardware such as the NAO robot and support software, including Choregraphe, OpenCV to capture and process images, the SVM to classify objects in images, and the Python programming environment. Five robotic actions were studied and three modes. The experiments used one robot as the "viewer" and the second robot as the "subject" being analyzed. Results show that the visual communication system has an accuracy of 90% in correctly identifying the five movements. This research has shown an original solution, as a model that can enable robots to run in the complex service tasks consisting of multiple connected actions in a dynamic environment. This methodology can also let the intelligent operation of the robots serve in different scenes according to their actual requirements. This research focuses on enhancing the prototype robot vision function and development of additional value for consolidation manageable platform that increases service robots in the home environment of intelligent control capability.

关键词： Anthropomorphic communication Dual-robots Visual communication Body posture Visual identification

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A sensor review for human detection with robotic systems in regular and smoky environments

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INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS 2023年第3期20卷

作者： Gelfert, Sebastian Munster Technol Univ Dept Elect & Elect Engn Cork Ireland Munster Technol Univ Dept Elect & Elect Engn Cork T12 P928 Ireland

Search and rescue robots gained a significant attention in the past, as they assist firefighters during their rescue missions. The opportunity to move autonomously or remotely controlled with intelligent sensor technology, to detect victims in unknown fire smoke environments, introduces a growing technology in fire engineering. Since sensor systems are a component of mobile robots, there is a demand for intelligent robot vision, especially for human detection in fire smoke environments. In this article, an overview of sensor technologies and their algorithms for human detection in regular and smoky environments is presented. These sensor technologies are categorized into single sensor and multi-sensor systems. Novel sensor approaches are led by artificial intelligence, 3D mapping and multi-sensor fusion. The article provides a contribution for future research directions in algorithms and applications and supports decision-makers in fire engineering to get knowledge in trends, novel applications and challenges in this field of research.

关键词： computer vision deep learning firefighting human detection mobile robot search and rescue sensor fusion smoky environment

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Comparison of Indoor Position Recognition Accuracy Using Grid Pattern Tracking Autonomous Mobile Robot

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JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY 2025年第5期20卷 3683-3696页

作者： Kim, Ki-Hyun Choi, Sang-Yule Choi, Jae-Hoon Kim, Jung-Ju Hoseo Univ Dept Automot ICT Cheonan South Korea Induk Univ Dept Mechatron Engn Seoul South Korea Hoseo Univ Dept Robot Cheonan South Korea Hoseo Univ Dept Intelligent Robot Cheonan South Korea

Existing studies on indoor position recognition employ diverse evaluation methods, which complicates direct accuracy comparisons across techniques. To address this issue, this study proposes a novel framework for evaluating the accuracy of indoor position recognition methods. The proposed framework evaluates accuracy by using the position recognition results of a grid-pattern-tracking autonomous mobile robot (GPT-AMR) as a benchmark. To validate the proposed evaluation method, a comparative analysis was conducted on four position recognition algorithms: (1) a computer vision-based algorithm, (2) a Bluetooth Low Energy (BLE)-based trilateration algorithm, (3) a BLE-based adaptive trilateration algorithm, and (4) a least squares method (LSM)-based algorithm. Experimental results demonstrated that the proposed evaluation method, which employs GPT-AMR, offers improved speed, accuracy, and practical applicability compared to conventional approaches. Furthermore, this method enables objective comparisons and evaluations of a wide range of indoor position recognition technologies, including both computer vision- and BLE-based algorithms, using a standardized criterion. Future research will focus on systematically validating the generalizability of the proposed method across different indoor environments and operational conditions. This study aims to advance indoor position recognition technology for autonomous mobile robots (AMRs) and improve their applicability in various service robotics domains.

关键词： Autonomous mobile robot Indoor position recognition Bluetooth low energy Trilateration Least squares method Adaptive trilateration

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DVRP-MHSI: Dynamic Visualization Research Platform for Multimodal Human-Swarm Interaction

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IEEE ROBOTICS AND AUTOMATION LETTERS 2025年第6期10卷 5665-5672页

作者： Zhu, Pengming Zeng, Zhiwen Yao, Weijia Dai, Wei Lu, Huimin Zhou, Zongtan Natl Univ Def Technol Coll Intelligence Sci & Technol Changsha 410073 Peoples R China Hunan Univ Sch Robot Changsha 410012 Peoples R China

In recent years, there has been a significant amount of research on algorithms and control methods for distributed collaborative robots. However, the emergence of collective behavior in a swarm is still difficult to predict and control. Nevertheless, human interaction with the swarm helps render the swarm more predictable and controllable, as human operators can utilize intuition or knowledge that is not always available to the swarm. Therefore, this letter designs the Dynamic Visualization Research Platform for Multimodal Human-Swarm Interaction (DVRP-MHSI), which is an innovative open system that can perform real-time dynamic visualization and is specifically designed to accommodate a multitude of interaction modalities (such as brain-computer, eye-tracking, electromyographic, and touch-based interfaces), thereby expediting progress in human-swarm interaction research. Specifically, the platform consists of custom-made low-cost omnidirectional wheeled mobile robots, multitouch screens and two workstations. In particular, the mutitouch screens can recognize human gestures and the shapes of objects placed on them, and they can also dynamically render diverse scenes. One of the workstations processes communication information within robots and the other one implements human-robot interaction methods. The development of DVRP-MHSI frees researchers from hardware or software details and allows them to focus on versatile swarm algorithms and human-swarm interaction methods without being limited to predefined and static scenarios, tasks, and interfaces. The effectiveness and potential of the platform for human-swarm interaction studies are validated by several demonstrative experiments.

关键词： robots Robot vision systems Cameras Visualization Mobile robots Heuristic algorithms Electromyography Workstations Universal Serial Bus Tracking Human-centered automation multi-modal perception for HRI multi-robot systems semi-physical

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Recent Advances in Robot Visual SLAM

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Recent Advances in computer Science and Communications 2023年第8期16卷 19-37页

作者： Zhang, Hongxin Jin, Hui Ma, Shaowei Robotics & ITS Engineering Research Center Harbin University of Science and Technology No. 52 Xuefu Road Nangang District Heilongjiang Harbin150080 China

Background: SLAM plays an important role in the navigation of robots, unmanned aeri-al vehicles, and unmanned vehicles. The positioning accuracy will affect the accuracy of obstacle avoidance. The quality of map construction directly affects the performance of subsequent path planning and other algorithms. It is the core algorithm of the intelligent mobile application. There-fore, robot vision SLAM has great research value and will be an important research direction in the future. Objective: By reviewing the latest development and patent of computer vision SLAM, this paper provides references to researchers in related fields. Methods: computer vision SLAM patents and literature were analyzed from the aspects of the algorithm, innovation, and application. Among them, there are more than 30 patents and nearly 30 pieces of literature in the past ten years. Results: This paper reviews the research progress of robot visual SLAM in the last 10 years, sum-marizes its typical features, especially describes the front part of the visual SLAM system in detail, describes the main advantages and disadvantages of each method, analyses the main problems in the development of robot visual SLAM, prospects its development trend, and finally discusses the related products and patents research status and future of robot visual SLAM technology. Conclusion: The Robot vision SLAM can compare the texture information of the environment and identify the difference between the two environments, thus improving accuracy. However, the cur-rent SLAM algorithm is easy to fail in fast motion and highly dynamic environments, most SLAM action plans are inefficient, and the image features of VSLAM are too distinguishable. Furthermore, more patents on the Robot vision SLAM should also be invented. © 2023 Bentham Science Publishers.

关键词： computer vision

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A Comprehensive Survey of Image Augmentation Techniques for Deep Learning

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PATTERN RECOGNITION 2023年第1期137卷

作者： Xu, Mingle Yoon, Sook Fuentes, Alvaro Park, Dong Sun Jeonbuk Natl Univ Dept Elect Engn Jeonbuk 54896 South Korea Mokpo Natl Univ Dept Comp Engn Jeonnam 58554 South Korea Jeonbuk Natl Univ Core Res Inst Intelligent Robots Jeonbuk 54896 South Korea

Although deep learning has achieved satisfactory performance in computer vision, a large volume of im-ages is required. However, collecting images is often expensive and challenging. Many image augmenta-tion algorithms have been proposed to alleviate this issue. Understanding existing algorithms is, therefore, essential for finding suitable and developing novel methods for a given task. In this study, we perform a comprehensive survey of image augmentation for deep learning using a novel informative taxonomy. To examine the basic objective of image augmentation, we introduce challenges in computer vision tasks and vicinity distribution. The algorithms are then classified among three categories: model-free, model-based, and optimizing policy-based. The model-free category employs the methods from image process-ing, whereas the model-based approach leverages image generation models to synthesize images. In con-trast, the optimizing policy-based approach aims to find an optimal combination of operations. Based on this analysis, we believe that our survey enhances the understanding necessary for choosing suitable methods and designing novel algorithms.(c) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license ( http://***/licenses/by-nc-nd/4.0/ )

关键词： Image augmentation Deep learning Image variation Vicinity distribution Data augmentation computer vision

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A Novel computer vision Algorithm for Enhancing Image Recognition and Classification 6

A Novel Computer Vision Algorithm for Enhancing Image Recogn...

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6th IEEE International Conference on Power, intelligent Computing and Systems, ICPICS 2024

作者： Zhong, Herun School of Arts and Design Hubei University of Technology Wuhan430000 China

ISBN: (纸本)9798350374315

computer vision focuses on optimizing computers to understand and interpret visual data from photos or movies, while image recognition specializes in detecting and categorizing objects or patterns in photographs. Technological advancements have revolutionized the field of computer science and found applications in various fields such as robotics, healthcare, security, and entertainment. This article offers a comprehensive overview of the novel approaches of computer vision algorithms widely used in enhancing image recognition and classification. The discipline deals with extracting, analyzing, and understanding information from images or videos by developing algorithms that enable robots to see and comprehend visual information similar to humans. Image recognition primarily emphasizes automatic identification and categorization of objects or patterns in pictures. According to findings, significant developments have been made due to large datasets availability along with improvements in deep learning techniques leveraging enhanced processor power. Convolutional neural networks are now the dominant approach for image recognition problems within deep learning field attaining consistently high-performance levels across several benchmarks. © 2024 IEEE.

关键词： Convolutional neural networks

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A computer vision Algorithm for Path Planning in Mobile robots 22

A Computer Vision Algorithm for Path Planning in Mobile Robo...

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22nd IEEE Conference on Pervasive and intelligent Computing

作者： Ruggieri, Claudio Russo, Miriana Santoro, Corrado Santoro, Federico Fausto STMicroelect Syst Res & Applicat I-95121 Catania Italy Univ Catania Dept Math & Informat Catania Italy

ISBN: (纸本)9798331522759;9798331522742

In robotics, route planning is essential to ensure the safe and efficient movement of robots within the workplace. This process involves determining a trajectory, usually a series of points in the workspace, to achieve a specific goal. It is essential to consider criteria such as reducing the length of the route, the number of manoeuvres and the avoidance of obstacles. Route planning techniques generally require modelling the environment, representing both the structure and the obstacles (fixed or mobile), and the implementation of algorithms that generate the trajectory through the free areas of the environment. This approach often includes constructing a graph of possible trajectories and using minimum path search algorithms, such as A*. This article presents a route planning algorithm that uses Voronoi diagrams and uses artificial vision algorithms. In addition, a case study is described in which the proposed technique is applied to guide an automated system through a maze drawn on a whiteboard by a user.

关键词： path planning robotic systems virtual environment voronoi diagrams opencv

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