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检索条件"任意字段=18th International Conference on Control Automation Robotics and Vision"

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A Preliminary Evaluation of Static Tests to Detect Slip Using Tyre Strain Sensing System in Robotic Platforms

A Preliminary Evaluation of Static Tests to Detect Slip Usin...

引用

international conference on control, automation, robotics and vision

作者： Ali Farooq Lutfi Lutfi Tobias Low Andrew Maxwell Control and Systems Engineering Department University of Technology Baghdad Iraq Faculty of Health Engineering and Sciences University of Southern Queensland Toowoomba Australia

Wheel slip estimation is a determinant factor in improving performance of wheeled mobile robots. Conventional wheel slip estimation methods relied upon sensors which are far from the tyre-ground interface;hence, they required the use of approximated models and complex transformations. A modern method which directly measures tyre-ground contact quantities utilising in-tyre sensors helps develop accurate and direct wheel slip estimation techniques. In this paper, an optimum sensing system for small, non-pressurised robotic tyres is presented. Data processing algorithms are proposed to show possible techniques for deploying the readings of this system to estimate tyre forces and slip variables. these algorithms analyse the sensing system's measurements in both longitudinal and lateral directions with respect to the tyre direction of motion. Performance of the system is evaluated with static tests using a custom-built, bench-top rig. In these tests, different angular positions, vertical forces, and horizontal forces were tested. Results of these tests demonstrated that the system is capable of detecting tyre slip with a suffcient degree of consistency and robustness.

关键词： Tires Robot sensing systems Wheels Strain Mobile robots

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Classifying Neuromorphic Data Using a Deep Learning Framework for Image Classification

Classifying Neuromorphic Data Using a Deep Learning Framewor...

引用

international conference on control, automation, robotics and vision

作者： Roshan Gopalakrishnan Yansong Chua Laxmi R Iyer Institute for Infocomm Research Agency for Science Technology and Research (A*STAR) Singapore

In the field of artificial intelligence, neuromorphic computing has been around for several decades. Deep learning has however made much recent progress such that it consistently outperforms neuromorphic learning algorithms in classification tasks in terms of accuracy. Specifically in the field of image classification, neuromorphic computing has been traditionally using either the temporal or rate code for encoding static images in datasets into spike trains. It is only till recently, that neuromorphic vision sensors are widely used by the neuromorphic research community, and provides an alternative to such encoding methods. Since then, several neuromorphic datasets are obtained by applying such sensors on image datasets (e.g. the neuromorphic CALTECH 101) have been introduced. these data are encoded in spike trains and hence seem ideal for benchmarking of neuromorphic learning algorithms. Specifically, we train a deep learning framework used for image classification on the CALTECH 101 and a collapsed version of the neuromorphic CALTECH 101 datasets. We obtained an accuracy of 91.66% and 78.01% for the CALTECH 101 and neuromorphic CALTECH 101 datasets respectively. For CALTECH 101, our accuracy is close to the best reported accuracy, while for neuromorphic CALTECH 101, it outperforms the last best reported accuracy by over 10%. this raises the question of the suitability of such datasets as benchmarks for neuromorphic learning algorithms.

关键词： Neuromorphics Training Gray-scale Testing vision sensors Computer architecture

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Fuzzy-Model-Based Leader-Follower Consensus of Nonlinear Multi-Agent Systems with Input Saturation

Fuzzy-Model-Based Leader-Follower Consensus of Nonlinear Mul...

引用

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

作者： Xiaolu Liu Duxin Chen Yan-Wu Wang Huaicheng Yan School of Automation Huazhong University of Science and Technology Wuhan P. R. China School of Mathematics Southeast University Nanjing P. R. China Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education East China University of Science and Technology Shanghai P. R. China

this paper presents a fuzzy-model-based method for solving the consensus problem of a class of nonlinear multi-agent systems (MASs) with input saturation. Since each agent has nonlinear dynamics, the system is not asymptotically null controllable with bounded controls (ANCBC). therefore, the widely-used low-gain feedback method for designing consensus protocols of MASs with input saturation can no longer work. To this end, the Takagi-Sugeno (T-S) fuzzy model is adopted to formulate the error dynamics of those nonlinear follower agents with input saturation as well as a leader with time-varying states. Accordingly, by using the properties of convex hull, a set of invariance condition in the format of linear matrix inequality (LMI) is designed. Furthermore, by enlarging the shape reference set, the estimation of the attraction domain can be obtained. Simultaneously, by viewing the control gain as an extra free parameter in the LMI optimization procedure, the leader-follower consensus algorithm is proposed, which guarantees that all followers with input saturation can track the leader, and they can asymptotically reach consensus. Finally, numerical experiments validate the effectiveness of the proposed anti-saturation consensus algorithm.

关键词： automation Nonlinear dynamical systems STEM Actuators Symmetric matrices

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Multi-robotic arms automated production line

Multi-robotic arms automated production line

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international conference on control, automation and robotics (ICCAR)

作者： Jeng-Dao Lee Wei-Chuan Li Jyun-Han Shen Ching-Wei Chuang Automation Engineering Department National Formosa University Taiwan Yunlin County

In response to the booming industrial automation, three commonly used industrial robots including one parallel type robot, one gantry type robot, and two six-axis serial robots will be self-developed in this study. the six-axis robot arm can be controlled by using Kinematics method. Furthermore, a fifth-order-polynomials method is used to limit accelerations and velocity on each joint to achieve continuity. Arc path of the robotic arm can be achieved by the three-points-arc interpolation. therefore, trajectories for gluing path planning will be successfully generated. Moreover, vision devices are used to inspect the work pieces after the laser engraving. In addition, the storage system provides storage of unassembled and finished workpieces. Finally, the system integration of all equipment will be completed to achieve a customized multifunction gluing and assembly line by self-developed robotic arms.

关键词： Manipulators Service robots Kinematics automation Robot kinematics Production

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Tissue P systems with rule production/removal 18th

Tissue P systems with rule production/removal

引用

18th international conference on Membrane Computing, CMC 1018

作者： Pan, Linqiang Song, Bosheng Zhang, Gexiang Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Automation Huazhong University of Science and Technology WuhanHubei430074 China School of Electric and Information Engineering Zhengzhou University of Light Industry ZhengzhouHenan450002 China Robotics Research Center and Key Laboratory of Fluid and Power Machinery Xihua University Chengdu610039 China

ISBN: (纸本)9783319733586

Tissue P systems are computational models inspired by the way of biochemical substance movement/exchange between two cells or between a cell and the environment, where all communication (symport/antiport) rules used in a system are initially set up and keep unchanged during any computation. In this work, a variant of tissue P systems, called tissue P systems with rule production/removal (abbreviated as TRPR P systems) is considered, where rules in a system are dynamically changed during a computation, that is, at any computation step new rules can be produced and some existing rules can be removed. the computation power of TRPR P systems is investigated. It is proved that Turing universality is achieved for TRPR P systems with one cell, and using symport rules of length at most 1, antiport rules of length at most 2 or symport rules of length at most 2 and working in a maximally parallel manner. We further show that TRPR P systems with two cells, using symport rules of length at most 1, and working in a flat maximally parallel manner, are Turing universal. © 2018, Springer international Publishing AG.

关键词： Cells

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Feature-Based and Convolutional Neural Network Fusion Method for Visual Relocalization

Feature-Based and Convolutional Neural Network Fusion Method...

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international conference on control, automation, robotics and vision

作者： Li Wang Ruifeng Li Jingwen Sun Hock Soon Seah Chee Kwang Quah Lijun Zhao State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China Nanyang Technological University Singapore ST Electronics (Training & Simulation Systems) Pte Ltd Singapore

Relocalization is one of the necessary modules for mobile robots in long-term autonomous movement in an environment. Currently, visual relocalization algorithms mainly include feature-based methods and CNN-based (Convolutional Neural Network) methods. Feature-based methods can achieve high localization accuracy in feature-rich scenes, but the error is quite large or it even fails in cases with motion blur, texture-less scene and changing view angle. CNN-based methods usually have better robustness but poor localization accuracy. For this reason, a visual relocalization algorithm that combines the advantages of the two methods is proposed in this paper. the BoVW (Bag of Visual Words) model is used to search for the most similar image in the training dataset. PnP (Perspective n Points) and RANSAC (Random Sample Consensus) are employed to estimate an initial pose. then the number of inliers is utilized as a criterion whether the feature-based method or the CNN-based method is to be leveraged. Compared with a previous CNN-based method, PoseNet, the average position error is reduced by 45.6% and the average orientation error is reduced by 67.4% on Microsoft's 7-Scenes datasets, which verifies the effectiveness of the proposed algorithm.

关键词： Visualization Feature extraction Training Cameras Vocabulary Image retrieval Robots

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RCCNet: An Efficient Convolutional Neural Network for Histological Routine Colon Cancer Nuclei Classification

RCCNet: An Efficient Convolutional Neural Network for Histol...

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international conference on control, automation, robotics and vision

作者： S H Shabbeer Basha Soumen Ghosh Kancharagunta Kishan Babu Shiv Ram Dubey Viswanath Pulabaigari Snehasis Mukherjee Computer Vision and Machine Learning Groups Indian Institute of Information Technology Sri City Andhra Pradesh India

Efficient and precise classification of histological cell nuclei is of utmost importance due to its potential applications in the field of medical image analysis. It would facilitate the medical practitioners to better understand and explore various factors for cancer treatment. the classification of histological cell nuclei is a challenging task due to the cellular heterogeneity. this paper proposes an efficient Convolutional Neural Network (CNN) based architecture for classification of histological routine colon cancer nuclei named as RCCNet. the main objective of this network is to keep the CNN model as simple as possible. the proposed RCCNet model consists of 1, 512, 868 learnable parameters which are significantly less compared to the popular CNN models such as AlexNet, CIFAR-VGG, GoogLeNet, and WRN. the experiments are conducted over publicly available routine colon cancer histological dataset "CRCHistoPhenotypes". the results of the proposed RCCNet model are compared with five state-of-the-art CNN models in terms of the accuracy, weighted average F1 score and training time. the proposed method has achieved a classification accuracy of 80.61% and 0.7887 weighted average F1 score. the proposed RCCNet is more efficient and generalized in terms of the training time and data over-fitting, respectively.

关键词： Cancer Computer architecture Colon Biomedical imaging Task analysis Training Image analysis

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Manipulation of Lotus-root Fiber Based Soft Helical Microswimmers Using Rotating Gradient Field

Manipulation of Lotus-root Fiber Based Soft Helical Microswi...

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

作者： Meng Su Tiantian Xu Jia Liu Laliphat Manamanchaiyaporn Yanming Guan Zhiming Hao Xinyu Wu University of Chinese Academy of Sciences Beijing China Shenzhen Key Laboratory of Minimally Invasive Surgical Robotics and System Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Chinese Academy of Sciences Shenzhen China

Untethered and wirelessly-controlled microrobots have many applications in the field of biomedicine. therefore, many laboratories and scientists have invested more scientific research into magnetic microrobots which can make more contributions to medical care. Many magnetic field devices and microrobots are manufactured. In the development of micro-robots, helical microrobots have been well developed. Rigid-body robots account for the majority of these, but they may cause damage to human organs during treatment. However, soft and deformable robots can relieve more medical restrictions. In general, helical microrobots are driven by uniform fields which have their own limitations while the gradient magnetic field can relieve more restrictions and have more functions. this paper presents a flexible deformable helical swimmer controlled in a rotating gradient magnetic field. Helical swimmers are covered with magnetic nano-particles and the helical structure is derived from the inner fiber structure of the lotus root. the soft helical swimmers are controlled to swim several special trajectories in the rotating gradient magnetic field and we analyze the frequency and other factors for velocity or other effects.

关键词： Coils Magnetic hysteresis Robots Magnetic cores Soft magnetic materials Electromagnetics Torque

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Fractional Order Flight control of Quadrotor UAS: an OS4 Benchmark Environment and a Case Study

Fractional Order Flight Control of Quadrotor UAS: an OS4 Ben...

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

作者： Bo Shang Yunzhou Zhang Chengdong Wu YangQuan Chen College of Information Science and Engineering Northeastern University Shenyang China Faculty of Robot Science and Engineering Northeastern University China School of Engineering University of California Merced CA USA

the OS4 quadrotor is a classic quadrotor simulation platform. So far, many different kinds of controllers have been designed based on its plant model. Most of the research only provided a numerical simulation to verify their designed controllers. Only a few researches have put the proposed controllers back to OS4 quadrotor to verify, but they didn't share the project folder to let others continue their work. More open-source and well-documented codes are needed to accelerate the application of fractional order controllers in industry. this paper updated the OS4 folder for the latest MATLAB version. A case of study demonstrated the workflow to design a fractional order proportional derivative controller for the simulated drone. Comparisons showed that fractional order controllers perform better in a nonlinear system like OS4 than integer order PID controllers. An impulse disturbance scenario is also used as a testbed. Project folder can be accessed from: https://***/matlabcentral/fileexchange/67882-os4-foc. Related videos can be found from this link: https://***/heuz4tFqf64.

关键词： Mathematical model Drones Transfer functions Matlab Software packages Frequency control Estimation

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vision Based Automatic Landing with Runway Identification and Tracking

Vision Based Automatic Landing with Runway Identification an...

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international conference on control, automation, robotics and vision

作者： Amit Kumar Tripathi Vijay V Patel Radhakant Padhi Aeronautical Development Agency Bangalore India Faculty of Aerospace Engineering Indian Institute of Science Bangalore India

vision based autolanding of a fixed wing unmanned aerial vehicle (UAV) is presented in this paper. the UAV initially searches for a nearby unknown road or runway from the terrain image frames captured by onboard stereovision camera. the captured unknown road or runway are evaluated to be a possible candidate for autolanding of a UAV. Six degree of freedom (6DOF) simulink model of a UAV with landing and navigation autopilot is integrated with flightgear flight simulation software. Flightgear FG camera is used to capture image frames of the nearyby terrain while UAV is in auto navigation mode and performing a level flight with various heading angles to look out for all possible terrain scenario. Image processing techniques are applied on the captured video to identify a smooth and straight road or runway for landing and calculates the relative distance and orientation of the runway or road with respect to UAV's own location. Image processing techniques such as hough transform and random Sample consensus (RANSAC) are used to detect the road strip lines. Once the desired touchdown point on the road is computed as well as road heading is also computed, UAV begins the autolanding maneuver. the image processing techniques are used to identify the candidate road or runway. the heading of the runway and cross track of the runway is computed and autopilot is designed to bring the aircraft at desired touch down point on the road or runway.

关键词： Roads Cameras Unmanned aerial vehicles Image edge detection Silicon Aircraft

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