In this article, we investigate the viability of our proposed neural network-based extension of the “perception” control concept introduced by Randløv and Alstrøm. In their work, each of the expectation el...
In this article, we investigate the viability of our proposed neural network-based extension of the “perception” control concept introduced by Randløv and Alstrøm. In their work, each of the expectation elements is linearly acquired such that the expectation gives only the dominant information of the recent past. This handicap could become a serious problem when the perception process is applied to real physical systems. Such an approach has no capability to sense the trend or the dynamics in the information. Here, we introduce an extension of the perception control process by using a radial basis function feedforward neural network to learn the trend and the dynamics in the information queue. Through our simulations, we show that our neural network-based method is better than the conventional method.
In this survey paper, we describe the research of biomimetic machines that has been founded at the advanced integration division of SICE. This research committee aims at studying on biomimetic machines, which is not t...
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In this survey paper, we describe the research of biomimetic machines that has been founded at the advanced integration division of SICE. This research committee aims at studying on biomimetic machines, which is not the conventional bionics that fuses the bioengineering and the electronics, rather directs to the realization of a machine and a robot using several biomimetic technologies. We mainly discuss about biomimetic control, biomimetic perception, biomimetic robots and their applications.
A design method for neural network (NN) based feedforward controller in the framework of neurointerface is proposed for nonholonomic robots by applying a concept of virtual master-slave system, in which a master robot...
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A design method for neural network (NN) based feedforward controller in the framework of neurointerface is proposed for nonholonomic robots by applying a concept of virtual master-slave system, in which a master robot is assumed to have a stable inverse dynamical model that includes unknown physical parameters. A PD-based feedback compensator is simply added to the neurointerface to suppress an output deviation caused by the mapping error of NN. The effectiveness of the present approach is shown by a simulation for a tracking control problem of a nonholonomic mobile robot with two-independent driving wheels.
In this paper, a back propagation neural network (NN) is presented for the inverse kinematics of redundant manipulator with joint limits. Since the inverse kinematics has infinite number of joint angle vectors, a fuzz...
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In this paper, a back propagation neural network (NN) is presented for the inverse kinematics of redundant manipulator with joint limits. Since the inverse kinematics has infinite number of joint angle vectors, a fuzzy neural network (FNN) is designed to provide an approximate value for that vector. This vector is fed into the NN as a hint input vector to guide the output of the NN within the self-motion. This FNN is designed based on cooperatively controlled each joint angle in the sense that it stops the motion on the critical axis at its limit in the expense of more compensation from the most relaxed joint to accomplish the task. The joint velocity limits as well as the joint limits are incorporated in this method. Simulations are implemented based on four-link redundant manipulator to show the effectiveness of the proposed control system.
A backpropagation neural network (NN) is presented for the inverse kinematic problem to obtain a position control system for manipulators with multiple degrees-of-redundancy, where information provided from a laser tr...
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A backpropagation neural network (NN) is presented for the inverse kinematic problem to obtain a position control system for manipulators with multiple degrees-of-redundancy, where information provided from a laser transducer at the end-effector is used for planning the trajectory. A fuzzy reasoning system is designed to generate an approximate joint angle vector, because the inverse kinematics in this problem has infinite number of solution vectors. This vector is fed into the NN as a hint input vector rather than as a training vector to limit and guide the searching space. Simulations are implemented on a four-link redundant planar manipulator to show that the present control system is capable of tracking the planned trajectory while avoiding the collision.
This paper discusses the safety assurance, capability features, and user-friendliness of Internet-based telerobotics, in the sense that how these features could be incorporated in order to enhance teleoperator perform...
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This paper discusses the safety assurance, capability features, and user-friendliness of Internet-based telerobotics, in the sense that how these features could be incorporated in order to enhance teleoperator performance. A comprehensive set of safety features are incorporated to the interface to screen and accept only the safe commands from the remote operator while discarding risky commands. A laser pointer is used to help remote operator in perceiving self-location and navigation, whereas orientation control has been completely automated and synchronized to the position commands of the teleoperator. The effectiveness of these features has been demonstrated by playing telerobotic mini-golf.
In this paper, the TCP retransmission timer adjustment mechanism is approached from the system's theoretic point of view. TCP uses a simple recursive system identification algorithm to capture both time variant an...
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In this paper, the TCP retransmission timer adjustment mechanism is approached from the system's theoretic point of view. TCP uses a simple recursive system identification algorithm to capture both time variant and time invariant Internet behavior and provides a dynamic round-trip time (RTT) predictor. Based on real Internet data collection, it is observed that when the retransmission timer is adjusted by using the proposed predictor instead of the traditional RTT estimator, its performance increases significantly.
A cylindrical tactile sensor that can simultaneously measure a three-dimensional force based on multifunctional sensing technique is proposed. The central components of this sensor are two coils and a medium. A step-b...
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A cylindrical tactile sensor that can simultaneously measure a three-dimensional force based on multifunctional sensing technique is proposed. The central components of this sensor are two coils and a medium. A step-by-step method is used to realize multifunctional sensing, and in each step, a different physical quantity is sensed. On the basis of the unique structure of the sensor and ingenious measuring methods, the authors realize testing more than one physical quantity, that is, the magnitude and two direction angles of the contact force, with a single sensor. The paper discusses the design guideline for and the structure of the sensor, with deep inquiries into the step-by-step measuring method and experimental results.
This paper presents an exoskeleton for the assist of forearm motion (elbow flexion-extension and forearm pronationsupination motion) in daily activity and rehabilitation. The exoskeleton is controlled based on the act...
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This paper presents an exoskeleton for the assist of forearm motion (elbow flexion-extension and forearm pronationsupination motion) in daily activity and rehabilitation. The exoskeleton is controlled based on the activation patterns of the electromyogram (EMG) signals of the patient's muscles, which directly reflects the motion intention of the patient, in order to realize natural motion assist The sophisticated real-time neurofuzzy control method, in which the effect of a muscle common to both motions is taken into account, is proposed. The proposed control method enables the cooperative motion of elbow and forearm of the patient by learning the muscle activation patterns of each patient. The effectiveness of the proposed method was evaluated by experiment.
In walking of quadruped robots, a better performance is obtained by changing the order of swing leg at a gait. In this paper, we study a walking with obstacles avoidance of a quadruped robot using neural network (NN) ...
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In walking of quadruped robots, a better performance is obtained by changing the order of swing leg at a gait. In this paper, we study a walking with obstacles avoidance of a quadruped robot using neural network (NN) for determining the moving distance of the robot and for determining the order of a swing leg. The training data is considered with initial positions of each leg. The effectiveness of the present method is demonstrated with some experiments using TITAN-Vin.
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