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Progressive co-adaptation in human-machine interaction

Progressive co-adaptation in human-machine interaction

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international conference on Informatics in control, automation and robotics (ICINCO)

作者： Paolo Gallina Nicola Bellotto Massimiliano Di Luca Department of Architecture and Engineering University of Trieste Trieste Italy Lincoln Centre for Autonomous Systems University of Lincoln Lincoln U.K. Centre for Computational Neuroscience and Cognitive Robotics & School of Psychology University of Birmingham Birmingham U.K.

In this paper we discuss the concept of co-adaptation between a human operator and a machine interface and we summarize its application with emphasis on two different domains, teleoperation and assistive technology. the analysis of the literature reveals that only in a few cases the possibility of a temporal evolution of the co-adaptation parameters has been considered. In particular, it has been overlooked the role of time-related indexes that capture changes in motor and cognitive abilities of the human operator. We argue that for a more effective long-term co-adaptation process, the interface should be able to predict and adjust its parameters according to the evolution of human skills and performance. We thus propose a novel approach termed progressive co-adaptation, whereby human performance is continuously monitored and the system makes inferences about changes in the users' cognitive and motor skills. We illustrate the features of progressive co-adaptation in two possible applications, robotic telemanipulation and active vision for the visually impaired.

关键词： Training Robots Usability Monitoring Mice Man machine systems Uncertainty

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Adaptive Design of a Cyber-Physical System for Industrial Risk Management Decision Support

Adaptive Design of a Cyber-Physical System for Industrial Ri...

引用

international conference on control, automation, robotics and vision (ICARCV)

作者： Andrzej M.J. Skulimowski Paweł Łydek Decision Science Laboratory AGH University of Science and Technology Kraków Poland Progress & Business Foundation International Centre for Decision Sciences and Forecasting Kraków Poland Decision Science Laboratory AGH University of Science and Technology Chair of Automatic Control and Robotics Kraków Poland

ISBN: (纸本)9781665476881

this article presents an integrated design of intelligent decision support systems (DSSs) for industrial risk management. the need for this class of systems has been necessitated by resilience building and threat response planning problems faced by complex industrial installations in energy and mining sectors. the proposed DSS software architecture is AI-based and applies causal and anticipatory networks, multi-criteria analysis, information fusion and knowledge engineering techniques. the use of AI-tools follows the AI-alignment paradigm, where AI evolution provides clues regarding the most suitable techniques to solve anticipated industrial safety problems in different time scales. We propose a general scheme of industrial risk management which includes threats, sensors, information flows, and decision-making models. this scheme is complemented by the risk optimization module, which selects the actions and actuators to implement them. Signals received from sensors are fused and confronted with threat management scenarios contained in the knowledge base. the recommendations concerning prevention, protection, and threat mitigation measures are generated by the DSS and conveyed to human decision makers for approval. Selected actions can also be autonomously initiated. Previous activity assessments result on an improved configuration of sensors and actuators, as well as more effective first responder actions. threat and risk management modules of the DSS are linked by a sequential machine learning procedure, so that the results of prior decisions can be used to learn managerial preferences and parameters of risk mitigating scenarios.

关键词： Decision support systems Economics Decision making Cyber-physical systems Hazards Sensors Risk management

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Distance Measurement of Underwater Target Based on Stereo vision

Distance Measurement of Underwater Target Based on Stereo Vi...

引用

IEEE international conference on Cyber Technology in automation, control, and Intelligent Systems

作者： Sen Lin Wentao Li Cong Wang Yandong Tang State Key Laboratory of Robotics Chinese Academy of Sciences Shenyang China

An underwater object location method based on binocular stereo vision and artificial auxiliary interaction is proposed. Firstly, the calibration principle and basic model of binocular stereo vision are given, and the relationship between binocular disparity and depth is deduced in detail. then, a special underwater camera (Nano SeaCam) is used, and we can calibrate the camera directly underwater. After that, the parameters of the camera are obtained to rectify the underwater images. Further, according to the characteristics of underwater ROV (Remote Operated Vehicle), we use the method of artificial interaction to select the corresponding pixels of left and right view images, and then use the distance measurement algorithm to calculate the target distance. the experimental results show that this method can achieve the proper effect of measuring distance underwater, and the accuracy can meet the practical requirements, which is feasible and efficient.

关键词： Cameras Distance measurement Calibration Distortion Optical imaging Stereo vision Laser radar

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Hand-Eye Calibration of Surgical Robots Based on a BP Neural Network Optimized by Using an Improved Sparrow Search Algorithm

Hand-Eye Calibration of Surgical Robots Based on a BP Neural...

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international conference on control, automation, robotics and vision (ICARCV)

作者： Jiaqi Zhu Weibo Ning Ye Yuan Hongjiang Chen Weijun Zhou Yecheng Tan Shuxing He Jun Hu Zhun Fan Shantou University Shantou China Hospital of Medical College of Shantou University Shantou China

ISBN: (纸本)9781665476881

Hand-eye calibration methods for surgical robots are employed to derive a transformation between the robot's base motor and visual coordinate systems. Accurately completing hand-eye calibration procedures provides an important guarantee that a surgical robot will exhibit positioning and execution accuracy sufficient for assisting surgeons in successfully completing surgical procedures. To improve the accuracy of robot hand-eye calibration methods based on backpropagation neural network (BPNN) models, we propose a modified BP neural network optimized using the sparrow search algorithm for hand-eye calibration model (TSSABPNN), which can enhance population initialization by applying tent mapping. Furthermore, we also design a new sliding 3D calibration tool. the sparrow search algorithm exhibits good local exploration ability, and we introduce a tent map with ergodic characteristics to initialize the sparrow population information, which further improves the network's global search ability and convergence rate. Finally, we experimentally analyze four calibration models: TSSABP NN model, a BP NN model optimized using a genetic algorithm of simulated annealing (GASABPNN), an unoptimized BP NN model, and the traditional singular value decomposition method. the results indicate that the proposed TSSABP NN model exhibits the maximum calibration precision and best robustness and iteratively converges faster.

关键词： Analytical models Medical robotics three-dimensional displays Robot kinematics Sociology Artificial neural networks Robustness

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Hierarchical Decomposition and Prescribed Performance Bound based Adaptive control for Leader-Follower Formation of Uncertain Nonholonomic Mobile Robots

Hierarchical Decomposition and Prescribed Performance Bound ...

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international conference on control, automation, robotics and vision (ICARCV)

作者： Jiajun Shen Wei Wang Jinhu Lü Chao Deng School of Automation Science and Electrical Engineering Beihang University Beijing China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing China School of Electrical and Electronic Engineering Nanyang Technological University Singapore

ISBN: (数字)9781728177090

ISBN: (纸本)9781728177106

In this paper, the cooperative formation control problem is investigated for multiple two-wheeled mobile robots with unknown parameters. By combining the hierarchical decomposition and prescribed performance bound (PPB) technique, distributed adaptive formation controllers are designed based on dynamic surface control. It is proved in the Lyapunov sense that all the closed-loop signals are semi-globally bounded and the tracking error converges to a compact set, which can be made arbitrarily small by adjusting the design parameters appropriately. Furthermore, formation maintenance, connectivity preservation and collision avoidance can be achieved with the proposed control scheme. Simulations are also given to verify the effectiveness of the theoretical results.

关键词： Mobile robots Robot kinematics Wheels Collision avoidance Directed graphs Kinematics Information processing

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Robust Model Predictive control for Markovian Jump Systems with All Unstable Modes

Robust Model Predictive Control for Markovian Jump Systems w...

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international conference on control, automation, robotics and vision (ICARCV)

作者： Bin Zhang Yan Song University of Shanghai for Science and Technology Shanghai China

ISBN: (数字)9781728177090

ISBN: (纸本)9781728177106

In this paper, robust model predictive control (RMPC) problem is investigated for a class of Markovian jump systems with unstable modes under polytopic uncertainties and hard constraints. the transition probability matrix and a mode-dependent control strategy in the framework of RMPC are co-designed. Moreover, in order to design a switching rule for the mean-square stability of the jump system, an off-line design scheme is first proposed to guarantee the on-line mode-dependent model predictive controller design. For the “on-line” part, a set of mode-dependent state feedback controllers is designed to minimize an upper bound of the worst-case infinite horizon cost function in terms of the solutions to a series of linear matrix inequalities. Finally, an simulation example regarding the economic system is implemented to verify the effectiveness of the proposed design scheme.

关键词： Uncertainty Linear matrix inequalities Switches State feedback Predictive control Stability criteria Cost function

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Feature Extraction and Tracking of a Weld Joint for Adaptive Robotic Welding

Feature Extraction and Tracking of a Weld Joint for Adaptive...

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international conference on control, automation, robotics & vision

作者： R.P. Manorathna P. Phairatt P. Ogun T. Widjanarko M. Chamberlain L. Justham S. Marimuthu M. R. Jackson EPSRC Centre for Innovative Manufacturing in Intelligent Automation Wolfson School of Mechanical and Manufacturing Engineering Loughborough University Loughborough LE11 3TU UK

ISBN: (纸本)9781479952007

Recent advances in automation and sensor technology have enabled the use of industrial robots for complex tasks that require intelligent decision making. vision sensors have been the most successfully used sensor in many high value industrial applications. Over the recent years, weld seam tracking has been a topic of interest, as most of the existing robotic welding systems operate on basis of pre-programmed instructions. Such automated systems are incapable of adapting to unexpected variations in the seam trajectory or part fit-up. Applications such as tungsten inert gas (TIG) welding of aerospace components require high tolerances and needs intelligent decision making. Such decision making procedure has to be based on the weld groove geometry at any instance. In this study, a novel algorithm along with an automated system was developed for estimating the joint profile and path tracking of a three dimensional (3D) weld groove. A real-time position based closed-loop system was developed with a six axis industrial robot and a laser triangulation based sensor. the system was capable of finding the 3D weld joint profile and position in real-time, and make intelligent decisions accordingly. Raw data from a vision sensor was processed through a novel algorithm to obtain X and Z co-ordinates at an accuracy of 8.3μm and 43μm respectively at an acquisition speed of 2.5 profiles per second. the algorithm was also capable of measuring the weld gaps with an accuracy of 28μm. Finally, the developed system was successfully used for three dimensional seam tracking, and demonstrates an accuracy of ±0.5mm at a tracking a speed of 2mm/s.

关键词： Robot Welding Intelligence Tracking Laser vision

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Design and Feasibility Test of an Automatic Scraping Robot

Design and Feasibility Test of an Automatic Scraping Robot

引用

international conference on Autonomous Robots and Agents, ICARA

作者： Zhenmeng Cui Liang Han Guancheng Dong Yingze Lin Yangzhen Gao Shuaishuai Fan School of Mechanical Engineering Southeast University NanJing China

Scraping is a key technology in high-precision machine tool machining. Scraping can eliminate the accumulated tolerances and improve the assembly accuracy of the machine tool. Scraping is a time-consuming and tedious manual labor, which is usually conducted by experienced technician. To overcome these shortcomings, a novel automatic scraping robot was designed and tested in this study. the robot includes a 3-axis moving mechanism, a vision recognition system, a 3-D measurement system, and a control system. In this study, milling is used to simulate the shape of tool marks in the traditional scraping process. After a series of tests, the designed robot has been verified to be able to perform automatic scraping work. the workpiece scraped with this robot meets the standard of a high precision machine.

关键词： Motion planning automation Shape Robot kinematics Machine vision Milling Manuals

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control of thermal damage in grinding by digital signal processing of raw acoustic emission

Control of thermal damage in grinding by digital signal proc...

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international conference on control, automation, robotics and vision (ICARCV)

作者： P.R. De Aguiar E.C. Bianchi P.J.A. Serni P.N. Lanconi Eleclrical Engineering Department Brazil Mechanical Engineering Department Engineering Faculty of Bauru UNESP Sao Paulo Brazil

Grinding process is usually the last finishing process of a precision component in the manufacturing industries. this process is utilized for manufacturing parts of different materials, so it demands results such as low roughness, dimensional and shape error control, optimum tool-life, with minimum cost and time. Damages on the parts are very expensive since the previous processes and the grinding itself are useless when the part is damaged in this stage. this work aims to investigate the efficiency of digital signal processing tools of acoustic emission signals in order to detect thermal damages in grinding process. To accomplish such a goal, an experimental work was carried out for 15 runs in a surface grinding machine operating with an aluminum oxide grinding wheel and ABNT 1045 e VC131 steels. the acoustic emission signals were acquired from a fixed sensor placed on the workpiece holder. A high sampling rate acquisition system at 2.5 MHz was used to collect the raw acoustic emission instead of root mean square value usually employed. In each test AE data was analyzed off-line, with results compared to inspection of each workpiece for burn and other metallurgical anomaly. A number of statistical signal processing tools have been evaluated.

关键词： Digital signal processing Acoustic emission Finishing Manufacturing industries Manufacturing processes Shape control Error correction Cost function Signal processing Acoustic signal detection

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Searching for High Accuracy Mix-Bitwidth Network Architecture

Searching for High Accuracy Mix-Bitwidth Network Architectur...

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international conference on control, automation, robotics and vision (ICARCV)

作者： Haochong Lan Zhiping Lin Xiaoping Lai School of Electrical and Electronic Engineering Nanyang Technological University Singapore School of Automation Hangzhou Dianzi University Hangzhou China

ISBN: (数字)9781728177090

ISBN: (纸本)9781728177106

the quantization of deep neural networks has drawn great research interest as well as industrial support for its tremendous advantages on boosting the inference speed of convolutional neural network models, especially on resource-constrained devices. Emerging research work and software framework for low-bit quantization, i.e., quantization under 8 bits, also shows strong potential. However, extreme low-bit neural network, e.g., binary neural network (BNN), suffers from significant accuracy loss. A previous work tried to improve the performance of extreme low-bit neural networks by adjusting channel numbers but achieves a poor balance between accuracy and model size. Alternatively, adjusting bitwidth for each layer gains a higher return on accuracy with an acceptable increase in model size. In this work, we employ a genetic algorithm to find the optimal bitwidth assignation for layers in VGG-Small and ResNet18. Both searched mix-bitwidth network architectures achieve higher accuracy with lower time and memory consumption, compared to their fix-bitwidth counterparts. A further investigation on the combination of BNN and the intermediate layer of higher bitwidth is also conducted.

关键词： Quantization (signal) Neural networks Computer architecture Network architecture Computational modeling Acceleration Training

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