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Animated simulation of human-robot coordination with alternative voice command

Animated simulation of human-robot coordination with alterna...

引用

ieee International symposium on computational intelligence in Robotics and automation (CIRA)

作者： J.Y.S. Luh S. Srioon Clemson University Clemson SC USA

In animated simulation of human-robot coordination, the voice command is a useful feature to free the human operator's hand during the compliance control stage. The purpose of developing the simulation program is to perform the simulation before any physical experiments with robot hardware are conducted. The outcome of the simulation may give an insight into any unexpected interactions which may endanger the human operator as well as equipment. The human operator may learn from these experiences and be aware of the problems which may appear when physical experiments are performed.

关键词： Animation Humans Robot kinematics Object oriented modeling Robot sensing systems Grippers Wrist computational modeling Orbital robotics Hardware

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Design and analysis of one-step-ahead adaptive neural predictive controller

Design and analysis of one-step-ahead adaptive neural predic...

引用

ieee International symposium on computational intelligence in Robotics and automation (CIRA)

作者： Dianhui Wang T.S. Dillon A.K.Y. Wong Department of Computer Science and Computer Engineering La Trobe University Bundoora VIC Australia Department of Computing Hong Kong Polytechnic University Hung Hom Kowloon Hong Kong China

This paper aims at developing an adaptive one-step-ahead neural predictive control scheme for controlling nonlinear unknown systems. We here focus on two issues: controller design and performance analysis. A regularization cost function embodying the plant sensitivity information is proposed, which enhances the estimation accuracy of the plant Jacobian. The local linearization concept is applied to controller design. The control law is expressed explicitly with a variable parameter which may compensate for the error effect caused by the linear approximation in the neural model. The convergence theorem for neural predictor is obtained by the Lyapunov approach. The BIBO stability analysis of the closed-loop control system is also established.

关键词： Programmable control Adaptive control control systems Predictive control Nonlinear control systems Performance analysis Cost function Jacobian matrices Error correction Linear approximation

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An efficient neural controller for a nonholonomic mobile robot

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

引用

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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Joystick teaching system for polishing robots using fuzzy compliance control

Joystick teaching system for polishing robots using fuzzy co...

引用

ieee International symposium on computational intelligence in Robotics and automation (CIRA)

作者： F. Nagata K. Watanabe K. Kiguchi K. Tsuda S. Kawaguchi Y. Noda M. Komino Interior Design Research Institute Fukuoka Industrial Technology Center Fukuoka JAPAN Department of Advanced Systems Control Engineering Saga University Saga JAPAN ASA SYSTEMS INC. Fukuoka JAPAN

A joystick teaching system using a fuzzy compliance control is presented for polishing robots. The joystick is regarded as a virtual spring-damper system, so that the joystick's compliance in operation can be easily adjusted according to the friction force acting between the polishing tool and the workpiece. In conventional compliance control, both the damping coefficient and the stiffness coefficient are generally selected to be suitable for each task by trial and error. Our proposed method described suitably generates the component of stiffness by a simple fuzzy reasoning method. The effectiveness of the proposed system has been examined by some teaching experiments using an industrial robot FS-20 with a PC based controller.

关键词： Education Educational robots Fuzzy control Fuzzy systems control systems Friction Damping Error correction Fuzzy reasoning Electrical equipment industry

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Experience-based learning of task representations from human-robot interaction

Experience-based learning of task representations from human...

引用

ieee International symposium on computational intelligence in Robotics and automation (CIRA)

作者： M.N. Nicolescu M.J. Mataric Computer Science Department University of Southern California Los Angeles CA USA

We present an approach that allows a robot to learn task representations from its own experiences of interacting with a human. The robot follows a human teacher and maps its own observations of the environment into a representation of what has constituted the human's demonstration. The robot then builds a representation of the experienced task in the form of a behavior network. To enable this we introduce an architecture that extends the capabilities of behavior-based systems by allowing the representation and execution of complex and flexible sequences of behaviors. We demonstrate this architecture in a set of experiments in which a mobile robot learns representations for multiple tasks and is able to execute the tasks, even in changing environments.

关键词： Mobile robots Robotics and automation Human robot interaction Educational robots Computer architecture Computer science Education Automatic control Robustness Mars

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Humanoid walk control with feedforward dynamic pattern and feedback sensory reflection

Humanoid walk control with feedforward dynamic pattern and f...

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ieee International symposium on computational intelligence in Robotics and automation (CIRA)

作者： Qiang Huang Kejie Li Y. Nakamura Beijing Institute of Technology Beijing China Department of Mechano-Informatics University of Tokyo Japan

Since a biped humanoid inherently suffers from instability and always risks itself to tipping over, ensuring high stability and reliability of walk is one of the most important goals. This paper proposes a walk control consisting of a feedforward dynamic pattern and a feedback sensory reflex. The dynamic pattern is a rhythmic and periodic motion, which satisfies the constraints of dynamic stability and ground conditions, and is generated assuming that the models of the humanoid and the environment are known. The sensory reflex is a simple, but rapid motion programmed in respect to sensory information. The sensory reflex, we propose in this paper, consists of the body posture control, the actual ZMP (Zero Moment Point) control, and the landing time control. With the dynamic pattern and the sensory reflex, it is possible for the humanoid to walk rhythmically and to adapt itself to environmental uncertainties. The effectiveness of our proposed method was confirmed by walk experiments of an actual 26 DOF humanoid on an unknown rough terrain and in the presence of disturbances.

关键词： Feedback Reflection Humans Biological system modeling Humanoid robots Legged locomotion Mechatronics Stability Uncertainty Aging

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Repetitive robot visual servoing via segmented gained neural network controller

Repetitive robot visual servoing via segmented gained neural...

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ieee International symposium on computational intelligence in Robotics and automation (CIRA)

作者： Ping Jiang YangQuan Chen Dept of Informationand Control University of Tongji Shanghai China Center for Self-Organizing and Intelligent Systems (CSOIS) Dept of Electrical and Computer Engineering Utah State University Logan UT USA

The purpose of this paper is to design a neural network controller for a nonlinear system with uncertainties which are invariant or repetitive over repeatedly executed tasks such that the maximum tracking errors can be kept within a predefined region through an iterative learning or training process. The desired trajectory is segmented and for each segment a local neural network is constructed. The training of the local neural networks is done iteratively as the task repeats. Meanwhile, the training is segment-wise progressed from the starting segment to the ending one. The accurate tracking of the whole desired trajectory is thus accomplished in a step-by-step or segment-by-segment manner. As an application example, a robot visual servoing control problem is considered with an unknown system structure and camera parameters.

关键词： Visual servoing Neural networks control systems Nonlinear control systems Nonlinear systems Uncertainty Error correction Trajectory Robot control Robot vision systems

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Torque control of sinusoidal PMAC motors for direct-drive robots

Torque control of sinusoidal PMAC motors for direct-drive ro...

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ieee International symposium on computational intelligence in Robotics and automation (CIRA)

作者： Dong Sun J.K. Mills Department of Manufacturing Engineering and Engineering Management City University of Hong Kong Kowloon Hong Kong China Department of Mechanical and Industrial Engineering University of Toronto Toronto ONT Canada

A control approach for direct-drive robots with sinusoidal permanent magnet AC (PMAC) motors is developed. The conventional vector control for PMAC motors has been simplified by specifying the motor stator phase so that the rotating d-axis current is zero. This makes the motor work in maximum torque-per-amp operation. The proposed torque control, in the form of torque feedforward plus PI-type torque feedback, utilizes the feedback of nominal torque signal only, a signal that can be readily calculated, on-line. No torque sensor is required. Through proper design of the desired nominal torque with adaptive control technology, the proposed torque control can overcome the disturbances due to torque estimation error and model uncertainties. Experiments conducted on a commercial motion control system demonstrates the validity of the proposed approach in high-speed motions.

关键词： Torque control Permanent magnet motors Feedback Robot control AC motors Machine vector control Stators Adaptive control Estimation error Uncertainty

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Neural network detection and identification of actuator faults in a pneumatic process control valve

Neural network detection and identification of actuator faul...

引用

ieee International symposium on computational intelligence in Robotics and automation (CIRA)

作者： M. Karpenko N. Sepehri D. Scuse Department of Mechanical and Industrial Engineering University of Manitoba Winnipeg MAN Canada Department of Computer Science University of Manitoba Winnipeg MAN Canada

This paper establishes a scheme for detection and identification of actuator faults in a pneumatic process control valve using neural networks. First, experimental performance parameters related to the valve step responses, including dead time, rise time, overshoot, and the steady state error are obtained directly from a commercially available software package for a variety of faulty operating conditions. Acquiring training data in this way has eliminated the need for additional instrumentation of the valve. Next, the experimentally determined performance parameters are used to train a multilayer perceptron network to detect and identify incorrect supply pressure, actuator vent blockage and diaphragm leakage faults. The scheme presented here is novel in that it demonstrates that a pattern recognition approach to fault detection and identification, for pneumatic process control valves, using features of the valve step response alone, is possible.

关键词： Neural networks Fault detection Fault diagnosis Pneumatic actuators Process control Valves Steady-state Software packages Training data Instruments

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Improved path following of USU ODIS by learning feedforward controller using dilated B-spline network

Improved path following of USU ODIS by learning feedforward ...

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ieee International symposium on computational intelligence in Robotics and automation (CIRA)

作者： Yang Quan Chen K.L. Moore V. Bahl Center for Self-Organizing and Intelligent Systems (CSOIS) Department of Electrical and Computer Engineering UMC College of Engineering Utah State University Logan UT USA

A learning feedforward controller (LFFC) using a dilated B-splines network (BSN) is proposed in this paper. The LFFC acts as an add-on element to the existing feedback controller (FBC) for control performance enhancement. The LFFC signal is updated iteratively based on the FBC signal of previous iteration as the task repeats. In the LFFC approach, there are two parameters to tune: the B-spline support width and the learning gain. A frequency domain design approach is presented with detailed design formulae for dilation 2. Simulation results are presented for the path following control of the USU ODIS robot (omnidirectional inspection systems), a new family member of the Utah State University (USU) ODVs (Omni Directional Vehicles).

关键词： Spline Neural networks Feedforward neural networks control systems Adaptive control Robots Signal design Sampling methods Intelligent systems Intelligent networks

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