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Towards intelligent cooperative robotics in additive manufacturing: Past, present, and future

robotics AND COMPUTER-INTEGRATED MANUFACTURING 2025年 93卷

作者： Rescsanski, Sean Hebert, Rainer Haghighi, Azadeh Tang, Jiong Imani, Farhad Univ Connecticut Sch Mech Aerosp & Mfg Engn Storrs CT 06269 USA Univ Connecticut Dept Mat Sci & Engn Storrs CT 06269 USA Univ Illinois Dept Mech & Ind Engn Chicago IL 60608 USA

Additive manufacturing (AM) technologies have undergone significant advancements through the integration of cooperative robotics additive manufacturing (C-RAAM) platforms. By deploying AM processes on the end effectors of multiple robotic arms, not only are traditional constraints such as limited build volumes circumvented, but systems also achieve accelerated fabrication speeds, cooperative sensing capabilities, and in-situ multi-material deposition. Despite advancements, challenges remain, particularly regarding defect generation including voids, cracks, and residual stress. Various factors contribute to these issues, including toolpath planning (i.e., slicing strategies), part decomposition for cooperative printing, and motion planning (i.e., path and trajectory planning). This review first examines the critical aspects of system control for CRAAM systems consisting of slicing and motion planning. The methods for the mitigation of defects through the adjustment of these aspects and the process parameters of AM methods are then described in the context of how they modify the AM process: pre-process, inter-layer (i.e., during layer pauses), and mid-layer (i.e., during material deposition). The application of advanced sensing technologies, including high-resolution cameras, laser scanners, and thermal imaging, for capturing of micro, meso, and macro-scale defects is explored. The role of digital twins is analyzed, emphasizing their capability to simulate and predict manufacturing outcomes, enabling preemptive adjustments to prevent defects. Finally, the outlook and future opportunities for developing next-generation C-RAAM systems are outlined.

关键词： intelligent robotics Additive manufacturing Sensing and control Motion planning and slicing Digital twin

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intelligent robotics in 3D Simulation - An erobotics Approach

Intelligent Robotics in 3D Simulation - An eRobotics Approac...

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2nd International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Kaigom, Eric Guiffo Rossmann, Juergen Rhein Westfal TH Aachen Inst Man Machine Interact D-52074 Aachen Germany

ISBN: (纸本)9781479967735

Robot manipulators are increasingly employed in dynamic and uncertain environments. Therefore, weak and strong physical interactions with the surrounding operational environment can occur. Managing the complexity related to this trend requires simulation capabilities going far beyond traditional off-line motion planning of robots in free-space. This paper presents a dynamic simulation that addresses this issue. The simulator conveys insight into the accommodation of external forces during physical interaction, since the simulated robots are endowed with force-sensitive and compliance control capabilities. Further, a symbiotic simulation of compliance control enables physical interaction between a human operator and a real position-controlled robot. Our approach builds upon a comprehensive, holistic and versatile coupling of modeling paradigms. It leverages the significance of simulation outcomes by enriching the simulator with realistic robot control techniques. It deepens the understanding of ongoing processes by allowing an overall and customizable view on the robot down to actuators. The results highlight the effectiveness of the erobotics methodology, which represents the foundation this work is built upon.

关键词： control engineering computing digital simulation manipulators path planning 3D simulation compliance control dynamic simulation erobotics approach intelligent robotics position-controlled robot robot manipulators robot motion planning Admittance Impedance Joints Mathematical model Robot kinematics Robot sensing systems compliance control impedance Robot Manipulator control engineering computing Manipulator sensing systems Robot kinematics Dynamic simulation motion planning intelligent robots Digital simulation Computer Simulation Manipulators Path planning Robot Joints

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Brain-Inspired Visual Attention Modeling Based on EEG for intelligent robotics

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IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING 2024年第3期18卷 431-443页

作者： Hu, Shuzhan Duan, Yiping Tao, Xiaoming Chu, Jian Lu, Jianhua Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China State Key Lab Space Network & Commun Beijing 100084 Peoples R China

Vision, as the primary perceptual mode for intelligent robots, plays a crucial role in various human-robot interaction (HRI) scenarios. In certain situations, it is essential to utilize the visual sensors to capture videos for humans, assisting them in tasks like exploration missions. However, the increasing amount of video information brings great challenges for data transmission and storage. Therefore, there is an urgent need to develop more efficient video compression strategies to address this challenge. When perceiving a video, humans tend to pay more attention to some specific clips, which may occupy a small part of the whole video content, but largely affect the perceptual quality. This human visual attention (VA) mechanism provides valuable inspiration for optimizing video compression methods for HRI scenarios. Therefore, we combine psychophysiological paradigms and machine learning methods to model human VA and introduce it into the bitrate allocation to fully utilize the limited resources. Specifically, we collect electroencephalographic (EEG) data when humans watch videos, constructing an EEG dataset reflecting VA. Based on the dataset, we propose a VA measurement model to determine the VA states of humans in their underlying brain responses. Then, a brain-inspired VA prediction model is established to obtain VA metrics directly from the videos. Finally, based on the VA metric, more bitrates are allocated to the clips that humans pay more attention to. The experimental results show that our proposed methods can accurately determine the humans' VA states and predict the VA metrics evoked by different video clips. Furthermore, the bitrate allocation method based on the VA metric can achieve better perceptual quality at low bitrates.

关键词： Visual attention human-robot interaction intelligent robotics EEG video compression Visual attention human-robot interaction intelligent robotics EEG video compression

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Digitalisation and intelligent robotics in value chain of circular economy oriented waste management - A review

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WASTE MANAGEMENT 2019年 95卷 476-492页

作者： Sarc, R. Curtis, A. Kandlbauer, L. Khodier, K. Lorber, K. E. Pomberger, R. Univ Leoben Dept Environm & Energy Proc Engn Chair Waste Proc Technol & Waste Management Franz Josef Str 18 A-8700 Leoben Austria Univ Leoben Dept Environm & Energy Proc Engn Chair Proc Technol & Ind Environm Protect Franz Josef Str 18 A-8700 Leoben Austria

The general aim of circular economy is the most efficient and comprehensive use of resources. In order to achieve this goal, new approaches of Industry 4.0 are being developed and implemented in the field of waste management. The innovative K-project: Recycling and Recovery of Waste 4.0 - "ReWaste4.0" deals with topics such as digitalisation and the use of robotic technologies in waste management. Here, a summary of the already published results in these areas, which were divided into the four focused topics, is given: Collection and Logistics, Machines and waste treatment plants, Business models and Data Tools. Presented are systems and methods already used in waste management, as well as technologies that have already been successfully applied in other industrial sectors and will also be relevant in the waste management sector for the future. The focus is set on systems that could be used in waste treatment plants or machines in the future in order to make treatment of waste more efficient. In particular, systems which carry out the sorting of (mixed) waste via robotic technologies are of interest. Furthermore "smart bins" with sensors for material detection or level measurement, methods for digital image analysis and new business models have already been developed. The technologies are often based on large amounts of data that can contribute to increase the efficiency within plants. In addition, the results of an online market survey of companies from the waste management industry on the subject of waste management 4.0 or "digital readiness" are summarized. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Digitalisation intelligent robotics Waste management Circular economy Industry 4.0 Internet of Things ReWaste4.0 Waste treatment Smart waste factory

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Battery pack recycling challenges for the year 2030: Recommended solutions based on intelligent robotics for safe and efficient disassembly, residual energy detection, and secondary utilization

ENERGY STORAGE

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ENERGY STORAGE 2021年第3期3卷

作者： Zhou, Lin Garg, Akhil Zheng, Jun Gao, Liang Oh, Ki-Yong Huazhong Univ Sci & Technol Sch Mech Sci & Engn State Key Lab Digital Mfg Equipment & Technol Wuhan Peoples R China Chung Ang Univ Dept Energy Syst Engn Seoul South Korea

With the increasing use of batteries, battery recycling would become a considerable problem in the next decade. However, the current recycling technologies are still on the stage of research and development. A significant challenge in the traditional recycling method is that the recovery procedure relies heavily on manual work. Therefore, it is necessary to develop an intelligent, automatic or semi-automatic framework for rapid disassembly and efficient recovery of retired batteries. In this study, the key research problems during the battery recycling process were identified first. The main recycling process was divided into three parts: automatic disassemble process, residual energy detection, and second utilization as well as chemical recycling. Based on the above research gaps, a qualitative framework of UR5 robots for safe and fast battery recycling, residual energy detection, and secondary utilization of retired batteries was proposed. The framework includes a battery position and shape measurement system based on machine vision, an automatic battery removal system based on UR5 industrial robot, a battery residual energy detection, and classification system. Furthermore, a real case study of battery pack recycling was carried out based on manual work and automatic robot work. The results show that the proposed recycling framework can work efficiently compared with the traditional recycling method. Moreover, the future perspectives of battery recycling are summarized.

关键词： conservation of materials disassembly efficient recycling environmental benefits intelligent robotics recovery

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Changing Roles of intelligent robotics and Machinery Control Systems as Cyber-Physical Systems (CPS) in the Industry 4.0 Framework 2

Changing Roles of Intelligent Robotics and Machinery Control...

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2nd IEEE International Conference on Communication, Security and Artificial Intelligence, ICCSAI 2023

作者： Mohd, Noor Kumar, Indrajeet Khurshid, A.A. Graphic Era Deemed to Be University Dehradun Uttarakhand India Graphic Era Hill University Dehradun Uttarakhand India Shri Ramdeobaba College of Engineering and Management Nagpur India

ISBN: (纸本)9798350369960

intelligent robotics and machine learning are some of the major impactful disciples as they help to reduce the usage of electricity in the developing world and thus the roles of the intelligent and machinery control system are changing as the cyber-physical system in the industry 4.0 farm work. Proper and strong machinery control systems are being utilized to train the robots in order to enhance efficiency and accuracy. Artificial intelligence as well as machine learning upgrades the working efficiency of robotics and there is no sector that has been left. The changing roles of intelligent robotics and machinery system as cyber-physical system symbolizes (CPS) in the 4.0 framework industry. © 2023 IEEE.

关键词： Cyber-Physical Systems (CPS) Industry 4.0 framework intelligent robotics machinery control systems

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Information-Control Aspects of Sensor Systems for intelligent robotics

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IFAC Proceedings Volumes 1985年第16期18卷 11-16页

作者： J.L. Nevins The Charles Stark Draper Laboratory Inc. 555 Technology Square Cambridge MA 02139 USA

In order to discuss sensor systems in intelligent robotics or manufacturing systems it is necessary to classify tasks, controller requirements, as well as the information-control aspects. This paper classifies tasks as deterministic (principally driven by geometry considerations) and non-deterministic. The latter are the problems done by people requiring skill involving processes whose process models either do not exist or are poorly understood. Other non-deterministic tasks involve inspection or data interpretation. The process tasks require adaptive-learning type control systems and are rich in sensor needs. Automated inspection tasks can be implemented by Engineering-Based Expert systems with more modest sensor system requirements.

关键词： Adaptive-Learning Control Engineering-Based Expert Systems intelligent robotics intelligent Manufacturing Systems Robotic Sensor Systems automated robot grinding automated data interpretation

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Enhanced Flexibility and Reusability through State Machine-Based Architectures for Multisensor intelligent robotics

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SENSORS 2017年第6期17卷 1249-1249页

作者： Herrero, Hector Luis Outon, Jose Puerto, Mildred Salle, Damien Lopez de Ipina, Karmele Tecnalia Res & Innovat Ind & Transport Div San Sebastian 20009 Spain Univ Basque Country Euskal Herriko Unibertsitatea Dept Syst Engn & Automat EleKin Res Grp San Sebastian 20009 Spain

This paper presents a state machine-based architecture, which enhances the flexibility and reusability of industrial robots, more concretely dual-arm multisensor robots. The proposed architecture, in addition to allowing absolute control of the execution, eases the programming of new applications by increasing the reusability of the developed modules. Through an easy-to-use graphical user interface, operators are able to create, modify, reuse and maintain industrial processes, increasing the flexibility of the cell. Moreover, the proposed approach is applied in a real use case in order to demonstrate its capabilities and feasibility in industrial environments. A comparative analysis is presented for evaluating the presented approach versus traditional robot programming techniques.

关键词： intelligent robotics flexibility reusability multisensor state machine software architecture computer vision

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Adaptive Functional Module Selection using Machine Learning: Framework for intelligent robotics

Adaptive Functional Module Selection using Machine Learning:...

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SICE Annual Conference

作者： Martin Lukac Michitaka Kameyama Graduate School of Information Sciences Tohoku University

ISBN: (纸本)9784907764388

In robotics, it is a common problem that for a given task many algorithms are available. For a particular environmental context and some computational constraints some algorithms will perform better and others will perform worse. Consequently, a robot, evolving in a real world environment where both the context and the constraints change in real time, should be able to select in real time algorithms that will provide it with the most accurate world description as well as will allow it to extract the currently most vital information and artifacts. In this paper we propose a machine learning based approach for the real-time selection of computational resources (algorithms) based on both the high level objectives of the robot as well as on the low level environmental requirements (image quality, etc.). The learning mechanism described is using a Genetic Algorithm and the learning method is based on supervised learning;an initial set of algorithms with input data is provided as examples that are used for learning.

关键词： intelligent robotics Adaptive Algorithm Selection Machine Learning

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intelligent indoor metasurface robotics

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National Science Review 2023年第8期10卷 20-32页

作者： Hanting Zhao Shengguo Hu Hongrui Zhang Zhuo Wang Hao Dong Philipp del Hougne Tie Jun Cui Lianlin Li State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Center on Frontiers of Computing Studies School of Computer Science Peking University The French National Centre for Scientific Research(CNRS) University of Rennes State Key Laboratory of Millimeter Waves Southeast University

intelligent indoor robotics is expected to rapidly gain importance in crucial areas of our modern society such as at-home health care and factories. Yet, existing mobile robots are limited in their ability to perceive and respond to dynamically evolving complex indoor environments because of their inherently limited sensing and computing resources that are, moreover, traded off against their cruise time and payload. To address these formidable challenges, here we propose intelligent indoor metasurface robotics(I2MR),where all sensing and computing are relegated to a centralized robotic brain endowed with microwave perception; and I2MR's limbs(motorized vehicles, airborne drones, etc.) merely execute the wirelessly received instructions from the brain. The key aspect of our concept is the centralized use of a computation-enabled programmable metasurface that can flexibly mold microwave propagation in the indoor wireless environment, including a sensing and localization modality based on configurational diversity and a communication modality to establish a preferential high-capacity wireless link between the I2MR's brain and limbs. The metasurface-enhanced microwave perception is capable of realizing low-latency and high-resolution three-dimensional imaging of humans, even around corners and behind thick concrete walls, which is the basis for action decisions of the I2MR's brain. I2MR is thus endowed with real-time and full-context awareness of its operating indoor environment. We implement, experimentally, a proof-of-principle demonstration at ～2.4 GHz, in which I2MR provides health-care assistance to a human inhabitant. The presented strategy opens a new avenue for the conception of smart and wirelessly networked indoor robotics.

关键词： intelligent metasurfaces intelligent robotics edge devices IoT 6G

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