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检索条件"机构=Advanced Robotics and Intelligent Systems（ARIS） Lab.School of Engineering"

共 90 条记录，以下是61-70 订阅

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Biologically inspired tracking control of mobile robots with bounded accelerations

Biologically inspired tracking control of mobile robots with...

引用

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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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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Path planning of multi-robot systems with cooperation

Path planning of multi-robot systems with cooperation

引用

IEEE International Symposium on Computational Intelligence in robotics and Automation (CIRA)

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

In this paper, a novel gated dipole based approach is proposed for path planning of a multi-robot system, where the cooperative control strategy is based on the multi-agent systems. The system stability is guaranteed by a Lyapunov stability theory. The proposed approach is capable of generating collision-free paths for a multi-robot system in various situations, such as robots with different speed, with limited measurable sensor information, and in completely unknown environments. The effectiveness and efficiency of the proposed approach is demonstrated by simulation studies.

关键词： Path planning Multirobot systems Robot kinematics Orbital robotics Mobile robots intelligent robots Robot sensing systems Stability State-space methods Genetic algorithms

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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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Self-organizing behavior of a multi-robot system by a neural network approach

Self-organizing behavior of a multi-robot system by a neural...

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IEEE International Workshop on intelligent Robots and systems (IROS)

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

In this paper, a novel neural network approach to self-organizing behavior of a multi-robot system is proposed, which is capable of controlling a group of mobile robots to achieve multiple tasks at several different locations, such that the desired number of robots will arrive at every target location from any arbitrary initial robot locations. The proposed model is based on a self-organizing map (SOM) neural network. Unlike some conventional approaches to multi-robot path planning for multiple tasks where the task assignment and path planning are handled separately, this model combines the robot task requirement and motion planning together, such that the robots can start to move once the total tasks are set. The robot navigation can be dynamically adjusted to guarantee each target location will have the desired number of robots, even under unexpected uncertainties, such as one robot breaks down. In addition, unlike the conventional models that are suitable for static environment only, the proposed approach is also capable of dealing with changing environment. The effectiveness of the proposed approach is demonstrated by simulation studies.

关键词： Multirobot systems Neural networks Robot kinematics Mobile robots Robot sensing systems intelligent robots Path planning Control systems Costs intelligent systems

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Genetic algorithm based path planning for a mobile robot

Genetic algorithm based path planning for a mobile robot

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IEEE International Conference on robotics and Automation (ICRA)

作者： Jianping Tu S.X. Yang Advanced Robotics and Intelligent Systems ARIS Laboratory School of Engineering University of Guelph Guelph ONT Canada

In this paper, a novel genetic algorithm based approach to path planning of a mobile robot is proposed. The major characteristic of the proposed algorithm is that the chromosome has a variable length. The location target and obstacles are included to find a path for a mobile robot in an environment that is a 2D workplace discretized into a grid net. Each cell in the net is a gene. The number of genes in one chromosome depends on the environment. The locations of the robot, the target and the obstacle are marked in the workplace. The proposed algorithm is capable of generating collision-free paths for a mobile robot in both static and dynamic environments. In a static environment, the generated robot path is optimal in the sense of the shortest distance. The effectiveness of the proposed model is demonstrated by simulation studies.

关键词： Genetic algorithms Path planning Mobile robots Biological cells Fuzzy logic Evolutionary computation intelligent robots Employment Robot sensing systems Fuzzy systems

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A neuro-fuzzy approach to obstacle avoidance of a nonholonomic mobile robot

A neuro-fuzzy approach to obstacle avoidance of a nonholonom...

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

作者： Xiaochuan Wang S.X. Yang Advanced Robotics and Intelligent Systems (ARIS) Laboratory School of Engineering University of Guelph Guelph ONT Canada

In this paper, a neuro-fuzzy control system is developed for obstacle avoidance of nonholonomic mobile robot built in the aris lab. A combination of four infrared sensors is equipped to detect the distance to obstacles around the mobile robot. The distance information is processed by the proposed neuro-fuzzy controller to adjust the velocities of two separate driven wheels of the robot. Eighteen fuzzy rules are developed for the obstacle avoidance. Experiments demonstrate the effectiveness of the developed neuro-fuzzy controller.

关键词： Mobile robots Fuzzy logic intelligent robots Control systems Wheels Neural networks Automatic control Robot sensing systems Service robots Orbital robotics

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Tracking control of a nonholonomic mobile robot by integrating feedback and neural dynamics techniques

Tracking control of a nonholonomic mobile robot by integrati...

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Proceedings 2003 IEEE/RSJ International Conference on intelligent Robots and systems (IROS 2003) (Cat. No.03CH37453)

作者： Haowen Yang S.X. Yang G.S. Mittal Advanced Robotics and Intelligent Systems (ARIS) Laboratory School of Engineering University of Guelph Guelph ONT Canada

Mobile robots have been one of the challenging topics of control due to their nonholonomic property and restricted mobility. This paper presents the design of a novel tracking controller for a mobile robot by integrating the neural dynamics model into a conventional feedback controller. The proposed controller is capable of generating real-time smooth velocities, and driving the mobile robot to track desired trajectories. It resolves the speed jump problem existing in some previous tracking controllers. Lyapunov stability theory is used to prove the stability of the control system and the convergence of tracking errors to zero. The effectiveness of the proposed controller is demonstrated by simulation and comparison studies.

关键词： Mobile robots Neurofeedback Adaptive control Velocity control Trajectory Lyapunov method Stability Control systems Convergence Error correction

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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...

引用

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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