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World Congress on intelligent control and Automation (WCICA)

作者： Xinde Li Xinhan Huang Min Wang Gang Peng Intelligent Control and Robotics Laboratory Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan China

Information acquired in map building presents characteristics of uncertainty, imprecision and even high conflict, especially in the course of building grid map using sonar. Here a new method of information fusion - DSmT (Dezert-Smarandache theory) recently developed from DST and Bayesian theory was introduced to apply to managing and dealing with this uncertainty. Aiming to static environment, classic DSm mathematic modal was established by constructing the general basic belief assignment function, so that the global evidence grid map is built by applying the classic DSm rule. Pioneer II virtual mobile robot served as an experiment platform. By comparing the numbers of acquiring-information spot, the quality of grid map building and the time in need of finishing the global map building, better fusion results than that with DST are gotten. Especially when dealing with high conflictive information from sonar grid map building, DSmT was more effective and successful than DST. In short, this study not only found a new method for building map under static environment, but also supplied with a theory foundation for us to further apply hybrid DSmT to dynamic unknown environment and multi-robots' building map together

关键词： Sonar Uncertainty intelligent robots Mobile robots Buildings Bayesian methods intelligent control Laboratories Mathematics Finishing

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Multiple Mobile Robots Map Building Based on DSmT

Multiple Mobile Robots Map Building Based on DSmT

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IEEE Conference on robotics, Automation and Mechatronics

作者： Peng Li Xinhan Huang Min Wang Xiangjin Zeng Intelligent Control and Robotics Laboratory Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan China

In this paper, a new multi-robot system framework is introduced to solve the problem of multi-robot map building. Compared with the classical architectures introduced in the literature, this kind of framework enhances overall system performance, especially in reducing calculations and communications, improving real-time performance. Meanwhile a general basic belief assignment function (gbbaf) is constructed to deal with the uncertain and imprecise information obtained by sonar sensors with the application of new information fusion method DSmT (dezert and smarandache theory) in the system and consideration of characteristics of sonar sensors. At last, Pioneer II mobile robots are used to carry out experiments of map building for both single-robot system and multi-robot system. The comparison of created ichnography with the real map testified the validity of DSmT and efficiency of multi-robot system for fusing imprecise information and map building proposed by this research.

关键词： Mobile robots Buildings Multirobot systems Sonar applications Sensor fusion Sensor phenomena and characterization Sensor systems and applications System performance Mobile communication Real time systems

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Neural Oscillator for Rhythmic Motion control of Biped Robot

Neural Oscillator for Rhythmic Motion Control of Biped Robot

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International Conference on Signal Processing, Communication and Networking (ICSCN)

作者： Carlos A. Acosta Calderon Mohan Rajesh Elara Changjiu Zhou Lingyun Hu Bharathiselvan Iniya Advanced Robotics and Intelligent Control Centre Advanced Robotics and Intelligent Control Centre Singapore polytechnics Singapore School ofElectrical and Electronics Department of Electronics and Communication Engineering SRM University Tamil Nadu India

This paper presents a structure of a neural oscillator which is used as Central Pattern Generator for a biped robot locomotion. This architecture is suitable to generate different rhythmic motions, according to the amplitude and frequency of the system. Results of the system on a simulated biped robot show the feasibility of this approach.

关键词： Oscillators Motion control Limit-cycles intelligent robots Signal generators Legged locomotion Neurons Humans Nonlinear dynamical systems intelligent control

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Robotic assistants for aircraft inspectors

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IEEE Instrumentation and Measurement Magazine 1998年第1期1卷 16-30页

作者： Siegel, Mel Gunatilake, Priyan Podnar, Gregg Intelligent Sensor Msrmt. C. Robotics Institute Carnegie Mellon University University of Colorado JILA University of Virginia SUNY Buffalo NY United States Extranuclear Laboratories ABB-Extrel Aircraft Diagnostics Corporation University of Alaska Fairbanks AK United States Elec. and Comp. Eng. Department Carnegie Mellon University CMU Vis. Lab. of the Robotics Institute CMU Mobile Robot Laboratory Engineering Design Research Center CMU Computer Science Department JiangXi University Robotics Institute Measurement and Control Laboratory

Various alternative aircraft inspection methods are first discussed and advantages of using robots are analysed. ANDI (Automated NonDestructive Inspector) and CIMP (Crown Inspection Mobile Platform) are then described. Remote 3D stereoscopic visual inspection is outlined and algorithms developed for crack detection and surface and subsurface corrosion detection are described. Future development trends are also outlined.

关键词： Robots Aircraft Aerospace electronics Instruments

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Fuzzy clustering involving convex polytopes

Fuzzy clustering involving convex polytopes

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Il Hong Suh Jae-Hyun Kim F. Chung-Hoon Rhee Intelligent Control and Robotics Laboratory Department of Electronic Engineering Hanyang University Ansan South Korea

Prototype based methods are commonly used in cluster analysis and the results may be highly dependent on the prototype used. In this paper, we propose a fuzzy clustering method that involves adaptively expanding convex polytopes. Thus, the dependency on the use of prototypes can be eliminated. Also, the proposed method makes it possible to effectively represent an arbitrarily distributed data set without a priori knowledge of the number of clusters in the data set. Specifically, nonlinear membership functions are utilized to determine whether a new cluster is created or which vertex of the cluster should be expanded. For this, the membership function of a new vertex is assigned according to not only a distance measure between an incoming pattern vector and a current vertex, but also the amount of how much the current vertex has been modified. Therefore, cluster expansion can be only allowed for one cluster per incoming pattern. Several experimental results are given to show the validity of our method.

关键词： Prototypes Clustering algorithms Phase change materials Shape Amorphous materials Fuzzy neural networks intelligent control intelligent robots Laboratories Design engineering

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Resilient Event-Triggered Model Predictive control for Adaptive Cruise control Under Sensor Attacks

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IEEE/CAA Journal of Automatica Sinica 2023年第3期10卷 807-809页

作者： Zhijian Hu Rong Su Kai Zhang Zeyuan Xu Renjie Ma School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore 639798Singapore Key Laboratory of Ultra-Precision Intelligent Instrumentation Ministry of Industry and Information Technologyand the Center of Ultra-Precision Optoelectronic Instrument EngineeringHarbin Institute of TechnologyHarbin 150001China Department of Control Science and Engineering Harbin Institute of TechnologyHarbin 150001China Department of Chemical and Biomolecular Engineering National University of SingaporeSingapore 117585Singapore State Key Laboratory of Robotics and Systems Harbin Institute of TechnologyHarbin 150001China IEEE

Dear Editor,This letter addresses the resilient model predictive control(MPC)problems for adaptive cruise control(ACC)systems under sensor *** the light of vulnerabilities of ACC systems to sensor attacks,an intrusion detection mechanism is proposed at the controller side to distinguish abnormal ***,the robust control gains are derived to design the terminal region constraint for MPC.

关键词： Trigger Event constraint

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Adaptive Block Elevation Mapping for Large-scale Scene

Adaptive Block Elevation Mapping for Large-scale Scene

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Zhou, Yang Zhu, Shiqiang Huang, Huang Li, Yuehua Gu, Jason The Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Laboratory Hangzhou311100 China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China The Beijing Institute of Control Engineering Beijing100094 China The Beijing Research Institute Zhejiang Laboratory Beijing100094 China The Department of Electrical and Computer Engineering Dalhousie University HalifaxNSB3H 4R2 Canada

ISBN: (纸本)9781665481090

Dense map that contains the surrounding geometry and vision information of a robot is widely used for path planning, navigation, obstacle avoidance and other applications. Considering the performance of the processing unit mounted on the robot is limited, mapping algorithm has to make compromise by sacrificing speed and precision. It will be more challenging when the dense mapping scene is very large because the memory consumption will be greatly increased and the map is difficult to be extended if beyonding the initial map. To suppress the negative impact from the increased map scale, we proposed a novel block mapping approach to generate the dense map in large scale of scene. In this work, the elevation map is selected as the base dense map. The entire elevation map is segmented into numerous block maps of which size is much smaller than that of the entire map. The present moment of lidar and vision measurements are used to generate the local elevation map. The local elevation map is used to update block maps which are adaptively generated along the motion trajectory. A memory-disk interaction mechanism, which the block maps will be loaded to memory or saved to local disk when needed, is introduced. Our block mapping approach is tested on the KITTI datasets, and the results demonstrate that the mapping approach can stably operate in a large scale of scene with a much smaller consumption of memory. © 2022 IEEE.

关键词： Motion planning

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Visual servoing of an autonomous Micro Air Vehicle for ground object tracking

Visual servoing of an autonomous Micro Air Vehicle for groun...

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2009 IEEE/RSJ International Conference on intelligent Robots and Systems

作者： Syaril Azrad Farid Kendoul Dwi Perbrianti Kenzo Nonami Robotics and Control Laboratory Department of Electronics and Mechanical Engineering Chiba University Chiba Japan

This paper describes an object tracking system using an autonomous micro air vehicle (MAV) and demonstrate its potential use for civilian purposes. The vision-based control system relies on a color and feature based vision algorithm for target detection and tracking, Kalman filters for relative pose estimation, and a nonlinear controller for MAV stabilization and guidance. The vision algorithm relies on information from a single onboard camera. An arbitrary target can be selected in real-time from the ground control station, thereby outperforming template and learning-based approaches. Experimental results obtained from outdoor flight tests, showed that the vision-control system enabled the MAV to track and hover above the target as long as the battery is available.

关键词： Visual servoing Land vehicles Remotely operated vehicles Road vehicles Mobile robots Target tracking Nonlinear control systems control systems Object detection Navigation

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Effects of a Dynamic Reference Frame in Mental Task Classification for EEG-Based Brain-Machine Interface

Effects of a Dynamic Reference Frame in Mental Task Classifi...

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IEEE Region 10 International Conference TENCON

作者： M. S. Abundo L. G. Sison Imstrumentation Robotics and Control Laboratory Department of Electronics Engineering University of Philippines Quezon Philippines

We study the effects of a moving reference frame on the classification of different mental tasks in a brain-machine interface (BMI). We use the band powers and power differences of the electroencephalogram (EEG) signals from 8 surface electrodes during 5 pre-determined mental tasks as the features for the neural network (NN) mental task classifier. We compare the NN classifier performance when the BMI user is visually subjected to a non-moving (static) reference frame (SRF) and to a moving (dynamic) reference frame (DRF) while performing the mental tasks. Results consistently show the degradation of classification accuracy for mental tasks when the user is in a DRF. Furthermore, we observe that mental tasks that require more focus are more sensitive to the SRF-DRF switch than those tasks which need less concentration when performed

关键词： Neural networks Switches Electroencephalography Electrodes Biological neural networks Degradation

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An intelligent coordinated control system for steering and traction of electric vehicles

An intelligent coordinated control system for steering and t...

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International Conference on Industrial electronics, control and Instrumentation

作者： M.K. Park I.H. Suh S.J. Byoun S.R. Oh Intelligent Control and Robotics Laboratory Department of Electronics Engineering Hanyang University Seoul South Korea Department of Control and Instrumentation Engineering Dong Yang University Youngju South Korea Division of Electronics Information Technology India

An intelligent coordinated control system is designed for the active steering and the left/right traction force distribution control of 2-wheel-drive and 2-wheel-steering (2WD/2WS) electric vehicles, where input-output linearization is employed. Also, a fuzzy-rule-based cornering force estimator is suggested to avoid using an uncertain highly nonlinear expression, and a neural network compensator is additionally utilized for the estimator to correctly find cornering force. With these techniques, the proposed control system is shown by simulation results to be robust against drastic change of the external environments such as road conditions.

关键词： intelligent systems intelligent control control systems Force control intelligent vehicles Electric vehicles Neural networks control system synthesis Robust control Roads

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