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REAL-TIME PATH PLANNING AND TRACKING CONTROL USING A NEURAL DYNAMICS BASED APPROACH

IFAC Proceedings Volumes 2002年第1期35卷 103-108页

作者： Simon X. Yang Eric Hu Advanced Robotics and Intelligent Systems (ARIS) Lab School of Engineering University of Guelph Guelph ON N1G 2W1 Canada

Real-time collision-free path planning and tracking control of a nonholonomic mobile robot in a dynamic environment is investigated using a neural dynamics based approach. The real-time robot path is generated through a dynamic neural activity landscape of a topologically organized neural network that represents the changing environment. The dynamics of each neuron is characterized by an additive neural dynamics model. The real-time tracking velocities are generated by a novel non-time based controller, which is based on the conventional event based control technique and an additive model. The effectiveness and efficiency of this approach are demonstrated through simulation and comparison studies.

关键词： mobile robots path planning obstacle avoidance velocity control neural dynamics neural network

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

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

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IEEE International Conference on systems, Man and Cybernetics

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

In this paper, fuzzy control laws for steering control of an autonomous nonholonomic mobile robot are designed and analyzed. 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 theoretically proved 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 fuzzy controller. The proposed fuzzy controller is also implemented on a nonholonomic mobile robot described by the model and the results show that the proposed fuzzy controller can achieve the desired turning angle and the autonomous mobile robot follows the target satisfactorily.

关键词： Fuzzy control Motion analysis Motion control Mobile robots Control systems Convergence Error correction Fuzzy systems Stability Turning

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From modern philosophy to intelligent robot

From modern philosophy to intelligent robot

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World Congress on intelligent Control and Automation (WCICA)

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

Thinking and intelligence can never be separated from the world. Modern philosophy rests on a new interpretation of the nature and fulfillment of human reason, and disputes about the nature of human reason are the ultimate battles of philosophy. The symbol based AI approach is not practical for real world problems. The world is artificial intelligence's best model. Intelligence can only be determined by the dynamics of interaction with the world. Being is a temporal event inseparable from the understanding of being embodied in Dasein's forms of life. Based on the modern philosophy's spirit, the behavior-based systems interact with real world directly. The constructed AI system based on philosophy has to express all its goals and desires as physical action to affect its environment, and extract all its knowledge from physical sensors. In this study, a fully autonomous mobile robot is built, after a thorough research to the philosophy's origin of the modern AI. In the mobile robot developed, each module itself generates behavior, and improvement in the competence of the system proceeds by adding new modules to the system. The performance of the robot proves that the whole system is stable.

关键词： intelligent robots Artificial intelligence Humans intelligent systems Sensor systems Mobile robots Cybernetics Machine intelligence Councils Casting

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Neural dynamics and computation for navigation of multiple robots

Neural dynamics and computation for navigation of multiple r...

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IEEE International Conference on systems, Man and Cybernetics

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

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Entire region filling in indoor environments using neural networks

Entire region filling in indoor environments using neural ne...

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World Congress on intelligent Control and Automation (WCICA)

作者： Chaomin Luo S.X. Yang M. Meng Advanced Robotics and Intelligent Systems (ARIS) Laboratory School of Engineering University of Guelph Guelph Canada Department of Electrical and Computer Engineering University of Alberta Edmonton Canada

Entire region filling is a special type of robot path planning strategy that requires the mobile robot to cover every part of the whole workspace, which has many applications such as cleaning robots, vacuum cleaners, painter robots, land mine detectors, lawn mowers, and window cleaners. In this paper, a novel biologically inspired neural network approach is proposed for entire region filling with obstacle avoidance of a mobile cleaning robot in a nonstationary environment. The dynamics of each neuron in the topologically organized neural network is characterized by a shunting equation or an additive equation derived from Hodgkin and Huxley's (1952) membrane equation. There are only local lateral connections among neurons. Thus the computational complexity linearly depends on the neural network size. The robot path is autonomously generated from the dynamic activity landscape of the neural network and the previous robot location. The proposed model algorithm is computationally efficient. It can deal with an unstructured environment with irregular obstacles. The effectiveness of the proposed model is demonstrated by simulation results.

关键词： Filling Indoor environments Neural networks Mobile robots Equations Cleaning Landmine detection Neurons Computational modeling Path planning

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Real-time area-covering operations with obstacle avoidance for cleaning robots

Real-time area-covering operations with obstacle avoidance f...

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IEEE/RSJ International Conference on intelligent Robots and systems

作者： Chaomin Luo S.X. Yang Xiaobu Yuan Advanced Robotics and Intelligent Systems (ARIS) Laboratory School of Engineering University of Guelph Guelph ONT Canada School of Computer Science Windsor University Windsor ONT Canada

An area-covering operation is a kind of complete coverage path planning, which requires the robot path to cover every part of the workspace, which is an essential issue in cleaning robots and many other robotic applications such as vacuum, robots, painter robots, land mine detectors, lawn mowers, and windows cleaners. In this paper, a novel biologically inspired neural network approach is proposed for complete coverage path planning with obstacle avoidance of a cleaning robot in a nonstationary environment. The dynamics of each neuron in the topologically organized neural network is characterized by a shunting equation or an additive equation derived from Hodgkin and Huxley's (1952) membrane equation. There are only local lateral connections among neurons. Thus the computational complexity linearly depends on the neural network size. The proposed model algorithm is computationally efficient, and can also deal with changing environment. Simulation results show that the proposed model is capable of planning collision-free complete coverage robot path.

关键词： Cleaning Robots Path planning Neural networks Equations Landmine detection Neurons Computational modeling Detectors Biomembranes

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A NEURAL COMPUTATION MODEL FOR REAL-TIME COLLISION-FREE ROBOT NAVIGATION

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IFAC Proceedings Volumes 2002年第1期35卷 323-328页

作者： Simon X. Yang Max Meng Hao Li Advanced Robotics and Intelligent Systems (ARIS) Lab School of Engineering University of Guelph Guelph ON N1G 2W1 Canada Advanced Robotics and Teleoperation (ART) Lab Department of Electrical and Computer Engineering University of Alberta Edmonton AB T6G 2G7 Canada

A biologically inspired neural computation model is proposed for dynamic planning and tracking control of robots. The dynamic environment is represented by a neural activity landscape of a topologically organized neural network, where each neuron is characterized by a shunting equation. The collision-free path is generated in real-time through the activity landscape without any prior knowledge of the dynamic environment. The real-time tracking control of robots to follow the planned path is also designed using shunting equations. The effectiveness is demonstrated through case studies. Simulation in several computer-synthesized virtual environments further demonstrates the advantages of the proposed approach.

关键词： path planning obstacle avoidance velocity control neural dynamics neural network

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A remote control system using Java and CORBA architecture

A remote control system using Java and CORBA architecture

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World Congress on intelligent Control and Automation (WCICA)

作者： Hao Li S.X. Yang Fangju Wang Advanced Robotics and Intelligent Systems (ARIS) Laboratory School of Engineering University of Guelph Guelph Canada Computing & Information Science Department University of Guelph Guelph Canada

Membranes hold promise as a new water treatment method of the future. In this study, a device is designed to test the efficiency of membranes. The device is implemented to be controlled remotely. An Internet based remote control system is implemented on the membrane test device to make the users access to it easier. When using the system, a remote operator only needs a general purpose computer with Internet connection to conduct a test. The engineering objective is to perform robust control over the Internet connection. A control architecture that combines computer and the membrane testing hardware is built. This system has two primary parts, the server part and the client part. A server is used to provide the application to the operator to control the hardware. The client part is executed on the remote operator's computer. The client uses a TCP/IP protocol to connect to the server through the Internet. Communication coordination between the client and the server is developed using Java and Common Object Request Broker Architecture (CORBA).

关键词： Control systems Java Biomembranes Internet Web server System testing Computer architecture Hardware Robust control Application software

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Tracking control of a mobile robot with kinematic and dynamic constraints

Tracking control of a mobile robot with kinematic and dynami...

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

作者： Heting Xu S.X. Yang ARIS (Advanced Robotics & Intelligent Systems) Lab School of Engineering University of Guelph Guelph ONT Canada

A path tracking control method with both kinematic and dynamic constraints is proposed for a nonholonomic mobile robot. By incorporating a biologically inspired shunting model into the conventional bang-bang control technique, the proposed tracking controller is capable of generating real-time acceleration commands that can produce smooth, continuous robot velocities, and drive the mobile robot to track the desired trajectories. In the controller design, the accelerations are bounded and the nonholonomic kinematic constraints are satisfied. The stability of the control system and the convergence of tracking errors to zero are proved using a Lyapunov stability theory. The effectiveness of the proposed tracking controller is demonstrated by simulation studies.

关键词： Mobile robots Kinematics Acceleration Biological system modeling Bang-bang control Velocity control Biological control systems Trajectory Stability Control systems

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An efficient neural controller for a nonholonomic mobile robot

An efficient neural controller for a nonholonomic mobile rob...

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

作者： Tiemin Hu S.X. Yang ARIS (Advanced Robotics & Intelligent Systems) Lab School of Engineering University of Guelph Guelph ONT Canada

In this paper, a novel neural network based controller is developed for real-time fine motion control of a nonholonomic mobile robot with completely unknown robot dynamics and under unmodeled disturbance. By taking advantage of the robot regressor dynamics that express the highly nonlinear robot dynamics in a linear form in terms of the robot dynamic parameters, the neural network consists of a single layer feedforward structure, and the learning algorithm is computationally efficient. Unlike previous works that use a typical backstepping velocity planner as the control input, a novel neural dynamics based velocity planner is used as input. The stability of the proposed control system and the convergence of tracking errors to zero are rigorously proved using the Lyapunov theory. The fine control of mobile robot is achieved through the online learning of the neural network without any off-line learning procedures. The effectiveness and efficiency of the proposed controller is demonstrated by simulation studies.

关键词： Mobile robots Neural networks Motion control Nonlinear dynamical systems Feedforward neural networks Computer networks Backstepping Velocity control Stability Control systems

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