The estimation of human behaviors by robots is one of key technologies in an environment in which humans and robots coexist. In this paper, a method is proposed for promptly estimating the behavioral targets by applyi...
The estimation of human behaviors by robots is one of key technologies in an environment in which humans and robots coexist. In this paper, a method is proposed for promptly estimating the behavioral targets by applying a fuzzy neural network (FNN). Here, inputs to the FNN are the human velocity, the angle of the human relative to an object, and the distance between the human and an object, whereas outputs are confidences that each object among all candidates is selected to be an intended object. The resultant human behavior can be estimated as a combination of the human action estimation and the behavioral target estimation.
This paper presents an alternative solution to simultaneous localization and mapping (SLAM) problem by applying a fuzzy Kalman filter using a pseudolinear measurement model of nonholonomic mobile robots. Takagi-Sugeno...
This paper presents an alternative solution to simultaneous localization and mapping (SLAM) problem by applying a fuzzy Kalman filter using a pseudolinear measurement model of nonholonomic mobile robots. Takagi-Sugeno fuzzy model based on an observation for a nonlinear system is adopted to represent the process and measurement models of the vehicle-landmark system. The complete system of the vehicle-landmark model is decomposed into several linear models. Using the Kalman filter theory, each local model is filtered to find the local estimates. The linear combination of these local estimates gives the global estimate for the complete system. The simulation results shows that the new approach performs better, though nonlinearity is directly involved in the Kalman filter equations, compared to the conventional approach.
In this paper, we propose an omnidirectional electric wheelchair (OEW). The proposed OEW has four omniwheels for the omnidirectional movement. Two of the omniwheels are arranged to X-axis direction and the other two a...
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In this paper, we propose an omnidirectional electric wheelchair (OEW). The proposed OEW has four omniwheels for the omnidirectional movement. Two of the omniwheels are arranged to X-axis direction and the other two are arranged to Y-axis direction. By controlling the movement of the omniwheels, the OEW can instantaneously rotate and move in all directions. Hence that, especially in the narrow spaced indoor environment, the omnidirectional nature of the OEW has an advantage over the standard wheelchair. Furthermore, the operatorpsilas posture is used as signal to the OEW. The operatorpsilas posture is measured by a ldquoZabuton sensorrdquo which uses a pressure sensor to measure the pressure distribution. The effectiveness of proposed the system is reflected by the experimental results of the prototype OEW and Zabuton sensor system.
Realization of cooperative behavior in multi-agent system is important for improving problem solving ability. Reinforcement learning is one of the learning methods for such cooperative behavior of agents. In this pape...
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ISBN:
(纸本)9781424437825
Realization of cooperative behavior in multi-agent system is important for improving problem solving ability. Reinforcement learning is one of the learning methods for such cooperative behavior of agents. In this paper, we consider pursuit problem for multi-agent reinforcement learning with communication between the agents. In our study, the agents obtain communication codes through learning. Here, the codes are rules for communicating appropriate information under various situations. We call the learning of communication codes signal learning. The signal is expressed by bit sequence, and its length is set to be variable. We carried out experiment for performance comparison with varying the signal length from 0 to 4 bits. As a result, it has been shown that, in learning precision, the case of 1 bit or more bits communication outperformed the case of no communication. It also has been shown that 4 bits communication produced the best result among the five cases, while learning with longer signals required much more iterations.
The paper presents passivity conditions for a class of stochastic Hopfield neural networks with state-dependent noise and with Markovian jumps. The contributions are mainly based on the stability analysis of the consi...
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ISBN:
(纸本)9789898111326
The paper presents passivity conditions for a class of stochastic Hopfield neural networks with state-dependent noise and with Markovian jumps. The contributions are mainly based on the stability analysis of the considered class of stochastic neural networks using infinitesimal generators of appropriate stochastic Lyapunov-type functions. The derived passivity conditions are expressed in terms of the solutions of some specific systems of linear matrix inequalities. The theoretical results are illustrated by a simplified adaptive control problem for a dynamic system with chaotic behavior.
A new control strategy is presented for a VTOL aerial robot with four rotors. A kinematics control law is first derived using Astolfipsilas discontinuous control, after introducing a chained form transformation with o...
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A new control strategy is presented for a VTOL aerial robot with four rotors. A kinematics control law is first derived using Astolfipsilas discontinuous control, after introducing a chained form transformation with one generator and three chains to the original model. This was motivated by the fact that the discontinuous kinematic-model without using a chained form transformation assures only a local stability of the kinematic based control system, instead of guaranteeing a global stability of the control system. Finally, a computer simulation is given to demonstrate the effectiveness of our approach.
A robotic forceps is controlled by voice instructions in the framework of a fuzzy coach-player system. In the proposed system, we can deal with some fuzziness included in voice instructions and the system is composed ...
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A robotic forceps is controlled by voice instructions in the framework of a fuzzy coach-player system. In the proposed system, we can deal with some fuzziness included in voice instructions and the system is composed of two instruction levels in order to increase the efficiency of voice instructions. One is a local instruction level that uses any action commands directly. The other is a global instruction level that uses a task command. Such a fuzzy coach-player system is applied for the manipulation of a robotic forceps and the effectiveness of the present system is verified through some actual experiments.
EEG arousals are seen in EEG records as awakening response of human brain. Obstructive sleep apnea (OSA) is one of serious sleep disorders. Sevier OSA brings about EEG arousals and sleep of patients with OSAS is frequ...
EEG arousals are seen in EEG records as awakening response of human brain. Obstructive sleep apnea (OSA) is one of serious sleep disorders. Sevier OSA brings about EEG arousals and sleep of patients with OSAS is frequently interrupted. Number of respiratory-related arousals during the whole night PSG recordings is directly concerned with the quality of patients’ sleep. Therefore, to detect EEG arousals in PSG record is significant task for clinical diagnosis. In this paper, the method for automatic detection of EEG arousals was proposed. In order to detected respiratory-related arousals effectively, threshold values were determined according to the pathological events as sleep apnea and EMG. If the resumption of ventilation (end of apnea) was detected, lower thresholds were adopted for detecting EEG arousals including relatively doubtful arousals. On the other hand, threshold maintains high when the pathological events were not detected. Proposed method was applied to the data of eight patients with OSAS, and accuracy of EEG arousals detection was verified by comparing the visual inspection. Effectiveness of the proposed method in clinical diagnosis was investigated.
The paper presents an ongoing investigation of applying finite state machines (FSM) to drive a meal assistance robot based on electromyogram (EMG) signals. An adapting single-threshold method on EMG power is proposed ...
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The paper presents an ongoing investigation of applying finite state machines (FSM) to drive a meal assistance robot based on electromyogram (EMG) signals. An adapting single-threshold method on EMG power is proposed to recognize different elevation gestures. Predefined control commands are output by FSM based on the extracted EMG features, and used to operate the robot. The performance of control mode is tested in efficiency and comfortableness by both subjective and objective indices. And the high performance of the EMG-control meal assistance robot makes it feasible for users with upper limbs motor disabilities.
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