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A FUSION MACHINE BASED ON DSMT AND PCR5 FOR ROBOT'S MAP RECONSTRUCTION

International Journal of Information Acquisition 2006年第3期3卷 201-211页

作者： XINHAN HUANG XINDE LI MIN WANG JEAN DEZERT Intelligent Control and Robotics Laboratory Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China ONERA 29 Av. de la Division Leclerc 92320 Chǎtillon France

Characteristics of uncertainty, imprecision, and even imperfection are presented from knowledge acquisition in map reconstruction using sonar sensors fixed on autonomous mobile robot. In order to improve the precision of the fusion and performances of map reconstruction, we propose in this paper a new fusion machine based on Dezert-Smarandache Theory (DSmT) coupled with the fifth Proportional Conflict Redistribution rule (PCR5) for dealing with uncertain and conflicting evidences provided by homogeneous or heterogeneous sources of information. We propose a belief model for sonar grid map and show how to construct efficiently generalized basic belief assignment functions for sensors onboard. A Pioneer II mobile robot with 16 sonar range finders serves as the experiment platform. In our experiment, the robot evolves in a real environment with some obstacles and the environment map is rebuilt online with our self-developing software platform. In this study, we also compare our new approach with other ones based on probability theory, fuzzy theory, Dempster-Shafer Theory (DST) and gray system theory. Our results show an improvement of the performances in precision of map reconstruction of mobile robot with respect to those obtained from aforementioned classical approaches.

关键词： Uncertainty DSmT grid map information fusion mobile robot PCR

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A New Architecture to Execute CAs-Based Path-Planning Algorithm in Mobile Robots

A New Architecture to Execute CAs-Based Path-Planning Algori...

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International Conference on Mechatronics (ICM)

作者： Adel Akbarimajd Caro Lucas Robotics and AI Laboratory Department of Electrical and Computer Engineering University of Tehran Iran Center of Excellence for Control and Intelligent Processing Department of Electrical and Computer Engineering University of Tehran Iran

Several path-planning algorithms for mobile robots have been introduced. Proper architectures for mobile robots to implement the path-planning algorithms are also of interest. If the mobile robots are to perform complicated tasks including complex sensing and planning operations and have accepted performance, must be autonomous: capable of acquiring information and performing tasks without programmatic intervention. In this paper we employ a layered architecture for mobile robots to perform our previously introduced cellular automata based path planning technique. It employs an abstraction approach which makes the complexity manageable. The architecture has an important feature which is its internal artifacts; it has some beliefs about the world and these beliefs are represented in artifacts and most actions are planned and performed with respect to these artifacts

关键词： Path planning Mobile robots Robot kinematics Content addressable storage Lattices Computer architecture Orbital robotics Automata intelligent sensors robotics and automation

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Neural adaptive control of dynamic sandwich systems with hysteresis

Neural adaptive control of dynamic sandwich systems with hys...

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IEEE International Conference on Computer-Aided Design

作者： Xinlong Zhao Yonghong Tan The Department of automatic control Shanghai Jiaotong University Shanghai China The Laboratory of Intelligent Systems and Control Engineering Guilin University of Electronic and Technology Guilin China

An adaptive control strategy is presented for dynamic sandwich systems with hysteresis. The so-called sandwich system with hysteresis is the system that can be represented by a cascade of a dynamic smooth nonlinear (DSNL1), a hysteresis nonlinear (HNL) and another dynamic smooth nonlinear (DSNL2) subsystem. In this control strategy, a neural network based inverse model is constructed to compensate for the effect of the first dynamic block (i.e. DSNL1) of the sandwich system. Thus, the sandwich system can be transformed into a dynamic nonlinear subsystem preceded by hysteresis. Then a novel hysteretic operator is proposed to transform the multi-valued mapping of hysteresis into a one-to-one mapping. Base on the proposed hysteretic operator, a neural adaptive controller is developed for the modified system. One of the advantages of the controller is that it does not need to construct the inverse model of hysteresis to cancel the hysteretic effect

关键词： Adaptive control Hysteresis Nonlinear dynamical systems control systems Inverse problems Programmable control Neural networks Optimal control Feedback control intelligent control

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Neural nets based modeling of inverse model for hysteresis using continuous transformation

Neural nets based modeling of inverse model for hysteresis u...

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IEEE International Conference on Computer-Aided Design

作者： Lianwei Ma Yonghong Tan Department of automatic control Shanghai Jiaotong University Shanghai China Laboratory of Intelligent Systems and Control Engineering Guilin University of Electronic and Technology Guilin China

This paper proposes a novel and simple approach for modeling of the inverse hysteresis. In this method, the continuous transformation technique is utilized to construct an elementary inverse hysteresis model (EIHM), which sets up a one-to-one mapping between the input space and the output space of the inverse hysteresis nonlinearity. Then the output of the EIHM is used as one of the input signals of the neural network (NN) to approximate the inverse behavior of hysteresis. Finally, the proposed method is applied to the modeling of the inverse model of hysteresis inherent in piezoelectric actuator

关键词： Inverse problems Neural networks Magnetic hysteresis Piezoelectric actuators intelligent control control system synthesis Artificial neural networks Oscillators Piezoelectric materials Magnetic levitation

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EHM Based Neural Model for Hysteresis

EHM Based Neural Model for Hysteresis

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IEEE International Conference on Networking, Sensing and control

作者： Lianwei Ma Yonghong Tan Laboratory of Intelligent Systems and Control Engineering Guilin University of Electronic and Technology Guilin China Department of Automation Shanghai JiaoTong University Shanghai China

This paper proposes a neural model for hysteresis. A method of continuous transformation is used to construct an elementary hysteresis model (EHM), which implements a one-to-one mapping between the input space and the output space of the hysteresis. The output of the EHM is used as one of the input signals of the neural network (NN) to approximate the behavior of hysteresis. A parabolic factor is introduced to improve the modeling performance for the major and minor loops of the hysteresis

关键词： Magnetic hysteresis Neural networks Piezoelectric actuators Magnetic levitation Degradation System performance System identification Oscillators Neurons intelligent systems

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Neurodynamics based Complete Coverage Navigation with Real-time Map Building in Unknown Environments

Neurodynamics based Complete Coverage Navigation with Real-t...

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2006 IEEE/RSJ International Conference on intelligent Robots and Systems

作者： Chaomin Luo Simon X. Yang Max Q.-h. Meng Advanced Robotics and Intelligent Systems Laboratory University of Guelph Guelph ONT Canada Department of Electronic Engineering Chinese University of Hong Kong New Territories Hong Kong China

A rectangular cell map representation and a neural dynamics based technique are proposed for real-time map building and complete coverage navigation (CCN) of a cleaning robot. The proposed model is compared with a triangular cell map based method proposed by Oh et al. (2004), which combined distance transform path planning, wall-following algorithm, and template based technique. Our method does not need any templates, even in unknown environments. A local map composed of rectangular cells is built through the proposed neural dynamics during CCN with restricted sensory information in unknown environments. The robot is able to dynamically build an accurate map of its immediate limited surroundings for its navigation. Comparison studies to triangular cell map based CCN approach show that the proposed model is capable of planning more reasonable and shorter coverage path in unknown environments

关键词： Neurodynamics Navigation Biomembranes Cleaning Robot sensing systems Path planning intelligent robots Biological system modeling Capacitance Real time systems

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Nonlinear Internal Model control for Hysteresis Systems

Nonlinear Internal Model Control for Hysteresis Systems

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IEEE International Conference on Networking, Sensing and control

作者： Yonghong Tan Miyong Su Laboratory of Intelligent Systems and Control Engineering Guilin University of Electronic and Technology Guilin China Department of Computer Science Guilin University of Electronic and Technology Guilin China Xidian University China

A hybrid model used to approximate hysteresis and creep nonlinear system is proposed. This model is constructed by a weighted superposition of both backlash operators and creep operators. Then, the corresponding inverse models for both hysteresis and creep are developed. Based on the obtained models, a nonlinear internal model control strategy is applied to the control of a system with hysteresis and creep nonlinearities

关键词： control system synthesis Nonlinear control systems Magnetic hysteresis Creep Piezoelectric actuators Neural networks Inverse problems control nonlinearities Feedforward neural networks Nonlinear systems

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Contrast-modulated Nonlinear Diffusion for X-ray Angiogram Images

Contrast-modulated Nonlinear Diffusion for X-ray Angiogram I...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Baopu Li Nong Sang Zhiguo Cao Department of Electronic Engineering Chinese University of Hong Kong Sha Tin Hong Kong China Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Wuhan China

In this paper, we present a new method for X-ray angiogram images enhancement using a contrast-modulated nonlinear diffusion. The original nonlinear diffusion is gradient driven, which leads into much dependence on the accurate estimation of the edge. However, it is very difficult to get the accurate estimation of edges for X-ray angiogram images, which are characterized with complex background. So it is necessary to do some improvements to this model. By designing a new concept of contrast space according to the characteristics of these images, we change the original nonlinear diffusion into contrast-modulated nonlinear diffusion. Compared with the traditional method, this new approach is proved to have a better performance of enhancement

关键词： X-ray imaging Anisotropic magnetoresistance Image processing Image analysis control engineering education intelligent control Image enhancement Biomedical imaging Medical diagnostic imaging Chemicals

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Real-time Path Planning of Mobile Robots in Dynamic Uncertain Environment

Real-time Path Planning of Mobile Robots in Dynamic Uncertai...

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World Congress on intelligent control and Automation (WCICA)

作者： Hui-zhong Zhuang Han Li Shu-xin Du Mechanical Electronical Engineering Department Vocational Technical College Shanghai University Engineering of Science Shanghai China Electronic Information Department Physics and Electronic Information College Wenzhou University Wenzhou Zhejiang China Institute of Intelligent Systems and Decision Making National Laboratory of Industrial Control Technology University of Zhejiang Hangzhou Zhejiang China

A new path planning method for mobile robots in globally unknown environment with moving obstacles is presented. With an autoregressive (AR) model to predict the future positions of moving obstacles, and the predicted position treated as instantaneously static, a motion path of the mobile robot is planned by means of a real-time path planning technique based on polar coordinates space in which the desirable direction angle is taken into consideration as an index of path optimization. Its effectiveness, feasibility, high stability, perfect performance of obstacle avoidance, real-time and optimization capability are demonstrated by simulation examples

关键词： Path planning Mobile robots Robot kinematics Predictive models Orbital robotics Hidden Markov models Navigation Real time systems Industrial electronics Educational institutions

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A support value transform-based multi focus image fusion method

A support value transform-based multi focus image fusion met...

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International Conference on Signal Processing Proceedings (ICSP)

作者： Sheng Zheng Jian Liu Guangxi Zhu Jinwen Tian Electronic & Information Engineering Department Huazhong University of Science and Technology Wuhan China College of Electrical Engineering & Information Technology China Three Gorges University Yichang China State Edu Commission Key Laboratory for Image Processing & Intelligent Control HUST Wuhan China Chinese Key laboratory of optic & electronics HUST Wuhan China

The image fusion is an important approach to produce a single complete image which preserves all relevant information from different sensors. In this paper, we proposed a support value transform-based multi focus image fusion method, where the fused saliency features are represented by support values. Based on the mapped least squares support vector machine, the support value transform is developed as a multi-scale analysis tool. The fusing results on the multi focus images demonstrate that the proposed image fusion method is effective and efficient

关键词： Focusing Image fusion Support vector machines Discrete wavelet transforms Optical sensors Image sensors Sensor fusion Support vector machine classification Image processing Least squares methods

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