This work presents a solution for distant control of industrial robots using mobile devices. The developed application can monitor the motion of the robot based on video and sensor information, it can send commands an...
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ISBN:
(纸本)9798350398823
This work presents a solution for distant control of industrial robots using mobile devices. The developed application can monitor the motion of the robot based on video and sensor information, it can send commands and control scripts to the robot, and it ensures the jogging-like manual control of the robot. In addition to the aforementioned functionalities, the application can analyze the teleoperation performances of the user. A set of performance metrics were introduced to rate user performances. They are useful to evaluate and educate remote manual robot control techniques. Experimental measurements are also presented to show the applicability of the developed remote control application and user performance evaluation method.
The Perceptual control Manifold is a recently introduced concept that extends the notion of the robot configuration space to include sensor feedback for robot motion planning. In this paper, we propose a framework for...
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ISBN:
(纸本)0818681381
The Perceptual control Manifold is a recently introduced concept that extends the notion of the robot configuration space to include sensor feedback for robot motion planning. In this paper, we propose a framework for sensor-based robot motion planning using the Topology Representing Network algorithm to develop a learned representation of the Perceptual control Manifold. The topology preserving features of the neural network lend themselves to yield after learning, a diffusion-based path planning strategy for flexible obstacle avoidance. Simulations on path control and flexible obstacle avoidance demonstrate the feasibility of this approach for motion planning and illustrate the potential for further robotic applications.
A methodology is developed for automatically tuning the main parameters of model predictive control (MPC) such as prediction horizon, control horizon and control interval. The tuning of parameters is done by means of ...
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Deep reinforcement learning is a focus research area in artificial intelligence. The principle of optimality in dynamic programming is a key to the success of reinforcement learning methods. The principle of adaptive ...
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This paper conducts simulations of reformation of mobile agents structure with analysis and provides a primitive but new method for automatic collision control. This dynamics is based on synchronization of coupled cha...
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ISBN:
(纸本)0780378660
This paper conducts simulations of reformation of mobile agents structure with analysis and provides a primitive but new method for automatic collision control. This dynamics is based on synchronization of coupled chaotic oscillators. The author applys this for agent simulator and verify the performance by agent's standpoint of view.
New open box and nonlinear model of Ultra High Frequency Polynomial and Sine Artificial Higher Order Neural Network (UPS-HONN) is presented in this paper. A new learning algorithm for UPS-HONN is also developed from t...
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ISBN:
(纸本)9781479945306
New open box and nonlinear model of Ultra High Frequency Polynomial and Sine Artificial Higher Order Neural Network (UPS-HONN) is presented in this paper. A new learning algorithm for UPS-HONN is also developed from this study. A control signal generating system, UPS-HONN Simulator, is built based on the UPS-HONN models. Test results show that, to generate any nonlinear control signal, average error of UPS-HONN models is under 1e-6.
The trajectory tracking control problem of nonholonomic mobile robots with parameter uncertainties has been analyzed. The kinematics and dynamical models of mobile robots are taken into account, the control rule based...
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ISBN:
(纸本)9781424448081
The trajectory tracking control problem of nonholonomic mobile robots with parameter uncertainties has been analyzed. The kinematics and dynamical models of mobile robots are taken into account, the control rule based on the kinematics model is taken as desired virtual control, and the adaptive sliding mode controller is designed, as the controller take into account both kinematics and dynamical model, the robot can not only track trajectory smoothly, but also be robust to parameter uncertainties. Based on Lyapunov theory, the system is stable. Finally, simulations are performed on the system with parameter uncertainties, and the results show that the proposed controller can track desired trajectory effectively.
The paper describes a Neuro Active Force control (NAFC) method that is applied to control a vertical moving mass (trolley) actuated by a fluidic muscle or pneumatic artificial muscle (PAM). The NAFC is in effect coupl...
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ISBN:
(纸本)9781424427529
The paper describes a Neuro Active Force control (NAFC) method that is applied to control a vertical moving mass (trolley) actuated by a fluidic muscle or pneumatic artificial muscle (PAM). The NAFC is in effect coupled to a proportional-integral-derivative (PID) controller and was practically implemented on a physical test rig that was developed in the laboratory. The effectiveness of the proposed controller was verified through the experiments, which suggests its superior performance in terms trajectory tracking control capability and disturbance suppression.
This paper proposes to shed a new light on the synthesis problem using the differential evolution algorithm. This algorithm allows optimizing simultaneously the structured controller and the dynamic (or static) D-scal...
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ISBN:
(纸本)9781479945306
This paper proposes to shed a new light on the synthesis problem using the differential evolution algorithm. This algorithm allows optimizing simultaneously the structured controller and the dynamic (or static) D-scalings, which leads to robust performance controllers. This method has been applied successfully to a classical flexible plant control problem. A comparison between the evolutionary approach and the non-smooth optimization one has been envisaged proving the high potential of the proposed method.
This paper proposes 1) Robot-Assisted Activity (RAA) to provide physical and mental support and 2) an emotion-driven control model for RAA. The construction of the control model uses hierarchical knowledge. A robot ca...
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ISBN:
(纸本)0780378660
This paper proposes 1) Robot-Assisted Activity (RAA) to provide physical and mental support and 2) an emotion-driven control model for RAA. The construction of the control model uses hierarchical knowledge. A robot can perform complex actions based on the robot's internal and external environmental information.
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