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IEEE International Conference on robotics and Automation (ICRA)

作者： Anmin Zhu S.X. Yang Advanced Robotics and Intelligent Systems (ARIS) Lab School of Engineering University of Guelph Guelph ONT Canada

In this paper, a novel fuzzy logic control system is developed for reactive navigation of a behavior-based mobile robot in dynamic environments. A combination of multiple sensors is equipped to sense the obstacles near the robot, the target location and the current robot speed. A fuzzy logic system with 48 fuzzy rules is designed, which consists of three behaviors: target seeking, obstacle avoidance and barrier following. The "symmetric indecision" problem is resolved by several mandatory-turn rules, while the "dead cycle" problem is resolved by a state memory strategy. Under the control of the proposed fuzzy logic model, the mobile robot can preferably "see" the environment around, and avoid static and moving obstacles automatically. The robot can generate reasonable trajectories toward the target in various situations without suffering from the "symmetric indecision" and the "dead cycle" problems. The effectiveness and efficiency of the proposed approach are demonstrated by simulation studies.

关键词： Fuzzy logic Navigation Mobile robots Robot kinematics Robot sensing systems intelligent robots Fuzzy systems Uncertainty Humans Fuzzy control

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VISUAL INFORMATION ACQUISITION IN VERTEBRATE RETINA

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International Journal of Information Acquisition 2004年第1期1卷 67-76页

作者： SIMON X. YANG Advanced Robotics and Intelligent Systems (ARIS) Lab School of Engineering University of Guelph Guelph ON N1G 2W1 Canada

In this paper, visual information acquisition in vertebrate retina is investigated using a novel neural network model. The neural network is based on the neural anatomy and function of retinal neurons in tiger salamander and mudpuppy. All the main types of retinal neurons are modeled, and their response characteristics are studied. The objective is to model the information acquisition in vertebrate retina with a simple yet effective neural network architecture. The model predictions on the main characteristics of retinal neurons are in agreement with the neurophysiological data. This study not only offers insight into the biological strategy and mechanism on the early visual information acquisition in vertebrate retina, but also has potential industrial applications such as VLSI chip design for efficient visual and movement sensors.

关键词： Visual information retinal neurons neural network neural dynamics

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Robotic uncalibrated hand-eye coordination based on the extended state observer

Robotic uncalibrated hand-eye coordination based on the exte...

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Asian Control Conference

作者： Jianbo Su Hongyu Ma Zhiwei Luo Research Center of Intelligent Robotics Shanghai Jiao Tong University Shanghai China Environment Adaptive Robotic Systems Lab RIKEN Nagoya Japan

ISBN: (纸本)0780388739

This paper proposes a standard control method to approach the uncalibrated robotic hand-eye coordination problem, which is system configuration- and task-independent. The coordination problem is first modeled by a dynamic system, where the unknown hand-eye relationship is regarded as system's modeling errors. An extended state observer is then designed to estimate impacts of this modeling error together with the system's external disturbances. With the estimation results as the compensation, the system control is thus accomplished based on a nonlinear combination of the system state errors. Experimental results are presented to verify the efficacy of the proposed approach and highlight the satisfactory performance.

关键词： Robot kinematics Control systems robotics and automation Jacobian matrices Observers State estimation Artificial neural networks Nonlinear control systems Automatic control Modeling

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intelligent obstacle avoidance for an autonomous mobile robot

Intelligent obstacle avoidance for an autonomous mobile robo...

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World Congress on intelligent Control and Automation (WCICA)

作者： Xiaochuan Wang S.X. Yang M.Q.-H. Meng Advanced Robotics and Intelligent Systems (ARIS) Lab School of Engineering University of Guelph Guelph ONT Canada Department of Electronic Engineering Chinese University of Hong Kong New Territories Hong Kong China

In this paper, an intelligent obstacle-avoidance approach to autonomous navigation of a mobile robot in unknown environments is developed using the neuro-fuzzy technique. A combination of four infrared sensors is equipped to detect the distance of obstacles around the mobile robot. The distance information is processed by the proposed neuro-fuzzy controller to adjust the velocities of the differential-drive system of the mobile robot. Simulation and experimental results demonstrate the effectiveness of the developed neuro-fuzzy controller.

关键词： intelligent robots Mobile robots Fuzzy logic Fuzzy systems Neural networks Navigation Control systems Orbital robotics Space exploration Fuzzy neural networks

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Neural dynamics based full-state tracking control of a mobile robot

Neural dynamics based full-state tracking control of a mobil...

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IEEE International Conference on robotics and Automation (ICRA)

作者： S.X. Yang Haowen Yang M.Q.-H. Meng Advanced Robotics and Intelligent Systems (ARIS) Lab School of Engineering University of Guelph Guelph ONT Canada Department of Electronic Engineering Chinese University of Hong Kong New Territories Hong Kong China

In this paper, a novel biologically inspired approach to real-time tracking control of a nonholonomic mobile robot is proposed. The proposed algorithm incorporates a neural dynamics model derived from a biological membrane equation with the conventional full-state tracking control technique. It is capable of generating real-time smooth and continuous velocity control signals that drive the mobile robot to follow desired trajectories. The proposed approach resolves the speed jump problem existing in some previous tracking controllers. In addition, it can track both continuous and discrete paths. The practicality and effectiveness of the proposed tracking controller were demonstrated by simulation and comparison results.

关键词： Mobile robots intelligent robots Neural networks Biological control systems Navigation Trajectory Robot control Feedback control Target tracking Polynomials

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Biologically inspired tracking control of mobile robots with bounded accelerations

Biologically inspired tracking control of mobile robots with...

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IEEE International Conference on robotics and Automation (ICRA)

作者： S.X. Yang A. Zhu M.Q.-H. Meng Advanced Robotics and Intelligent Systems (ARIS) Lab School of Engineering University of Guelph Guelph ONT Canada Department of Electronic Engineering Chinese University of Hong Kong New Territories Hong Kong China

In this paper, a novel biologically inspired tracking controller is proposed for real-time navigation of nonholonomic mobile robots, which is inspired by the agonist/antagonist effects in muscular sensory motor reaction of a gated dipole neural model. Through the incorporation of the biological computation element, the proposed controller is capable of generating smooth, bounded acceleration command signals for the mobile robot to track reference paths. It resolves the velocity jump problem in the conventional backstepping controllers that result from the initial tracking errors or the discontinuities in discrete paths. In addition, the proposed controller removes the unpractical assumption of "perfect velocity tracking" in some existing approaches. The effectiveness and efficiency of the proposed approach are demonstrated by simulation and comparison studies.

关键词： Robot control Biological control systems Mobile robots Acceleration Velocity control Navigation Biological system modeling Biology computing Signal generators Signal resolution

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An improved self-organizing map approach to traveling salesman problem

An improved self-organizing map approach to traveling salesm...

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IEEE International Conference on robotics, intelligent systems and Signal Processing

作者： Anmin Zhu S.X. Yang Advanced Robotics and Intelligent Systems (ARIS) Lab School of Engineering University of Guelph Canada

ISBN: (纸本)078037925X

In this paper, an improved self-organizing map approach to solving the traveling salesman problem is proposed by fixing the number of nodes in the output layer of neural network, modifying the neighborhood function, and modifying the weight update rules. An overview of previous work on solving the traveling salesman problem is given. An extension of the proposed algorithm can also be used to solve multiple traveling salesman problems and robot path planning. The simulation results demonstrate that the proposed algorithm is capable of providing a better solution within a reasonable time and much faster than conventional self-organizing map algorithms.

关键词： Traveling salesman problems Cities and towns Computer aided instruction intelligent robots intelligent systems Neural networks Path planning Costs Scheduling Books

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Analysis and design of an embedded fuzzy motion controller for a behavior-based nonholonomic mobile robot

Analysis and design of an embedded fuzzy motion controller f...

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IEEE International Symposium on intelligent Control (ISIC)

作者： Hao Li S.X. Yang Advanced Robotics and Intelligent Systems Lab School of Engineering University of Guelph Guelph ONT Canada

In this study, a fully autonomous mobile robot is built successfully by using the behavior-based artificial intelligence approach. Several levels of competences and behaviors are implemented. Each module itself in the developed mobile robot generates behaviors, and the improvement in the competence of the system proceeds by adding new modules to the system. Analysis and design of fuzzy control laws for steering control of the autonomous nonholonomic mobile robot are presented. The approach uses Lyapunov's direct method to formulate a class of control laws that guarantee the convergence of the steering error. Certain requirements for the control laws are presented for the designers to choose a suitable rule base for the fuzzy controller in order to make the system asymptotically stable. The stability of the proposed fuzzy controller is approached theoretically and also demonstrated by simulation studies. Simulations using the model of a four degree-of-freedom nonholonomic mobile robot are conducted to investigate the performance of the proposed fuzzy controller. The mobile robot can achieve the desired turn angle and follow the target satisfactorily.

关键词： Fuzzy control Motion analysis Motion control Mobile robots Control systems Artificial intelligence Navigation Robot control intelligent robots Convergence

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A biologically inspired approach to real-time tracking control of a mobile robot

A biologically inspired approach to real-time tracking contr...

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IEEE/ASME (AIM) International Conference on Advanced intelligent Mechatronics

作者： A. Zhu S.X. Yang Advanced Robotics and Intelligent Systems (ARIS) Lab School of Engineering University of Guelph Guelph ONT Canada

A novel tracking controller is proposed in this paper for real-time navigation of a nonholonomic mobile robot based on a neural dynamics model and a conventional backstepping model. By taking advantage of the features of the neural dynamics in a gated dipole model, the proposed controller is capable of generating smooth, continuous control signals to track a desired path. In addition, it can deal with arbitrarily large initial tracking errors. It resolves the velocity jump problem in conventional backstepping controllers resulted from sudden changes of tracking errors. The proposed approach is not very sensitive to model parameters and converges faster than a previous tracking control model. The effectiveness and efficiency of the proposed approach is demonstrated by a series of simulation and comparison studies.

关键词： Biological control systems Mobile robots Backstepping Torque control intelligent robots Sliding mode control Neural networks Error correction Robot control Real time systems

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Optimal control of supercritical fluid extraction with a hybrid model

Optimal control of supercritical fluid extraction with a hyb...

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IEEE International Symposium on intelligent Control (ISIC)

作者： Jin Zeng S.X. Yang Advanced Robotics and Intelligent Systems (ARIS) Lab School of Engineering University of Guelph Guelph ONT Canada

Supercritical fluid extraction is an environmental friendly separation technique in food and chemical industry. Optimal control is an essential issue in supercritical fluid extraction. The objective of this study is to improve the extraction processes to achieve the optimal performance in terms of a higher yield rate with a lower operating cost and a lower safety risk. In this paper, a hybrid control model combining the radial basis function network and the Peng-Robinson equation of state is used to model the supercritical fluid extraction process. An optimal control strategy is developed to select the process parameters. The effectiveness of the proposed control strategy is demonstrated by simulation studies.

关键词： Optimal control Chemical industry Mathematical model Predictive models Equations intelligent robots Cost function Radial basis function networks Separation processes Neural networks

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