The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this paper we described a sound-source localization (SSL) system which can be applied to mobile robot and automatic control systems. A novel approach of using artificial neural network was proposed to obtain the horizontal direction angle (azimuth) of the sound source. According to humanoid characteristic only two microphones, which were attached symmetrically on both sides of the robot as its...
In this study, an adaptive output recurrent cerebellar model articulation controller (AORCMAC) is investigated to control the two-wheeled robot. The main purpose is to develop a self-dynamic balancing and motion control strategy. The proposed AORCMAC has superior capability to the conventional cerebellar model articulation controller in efficient learning mechanism and dynamic response. The dynamic...
Mobile robots could play a significant role in places where it is impossible for the human to work. In such environments, neural networks, instead of traditional methods, are suitable solutions to locally navigate and recognize the environmentpsilas subspaces. In order to learn and perform two important functions ldquoenvironmental recognitionrdquo and ldquolocal navigationrdquo, multi-layered neural...
Light mobile robotpsilas weight design is a important problem which decides function and ability of mobile robot. In this paper, a total design method is advanced. There are many factors to consider, include mechanical part, electrical part, and task part. Each parts of robot must be carefully calculated and designed. There are many experiences in it. A light mobile robot is carefully analyzed as...
Several issues still need to be unraveled in the development of multiagent systems equipped with global vision, as in robot soccer leagues. Here, we underscore three of them (1) real-time constraints on recognition of scene objects; (2) acquisition of environment knowledge; and (3) distribution and allocation of control competencies shared between the repertoire of the agentpsilas reactive behavior,...
This study focuses on the design of a dynamic Petri recurrent-fuzzy-neural-network (DPRFNN) control for the path tracking of a nonholonomic mobile robot. In the DPRFNN, the concept of a Petri net (PN) and the recurrent frame of internal feedback loops are incorporated into a traditional fuzzy neural network (FNN) to alleviate the computation burden of parameter learning and to enhance the dynamic...
This paper presents an accurate localization scheme for mobile robots based on the fusion of an ultrasonic satellite (U-SAT) with inertial navigation system (INS), i.e., sensor fusion. Our aim is to achieve an accuracy of less than 100 mm. The INS consists of a yaw gyro and two wheel-encoders, and the U-SAT consists of four transmitters and a receiver. Besides the proposed localization method, we...
The trajectory tracking control problem of a tracked vehicle with slipping is considered in this paper. The slipping effects are analyzed and modeled as three time-varying parameters, which can be estimated simultaneously with robotpsilas pose using nonlinear estimators such as unscented Kalman filter. Dynamic feedback linearization integrated with a globally exponential stabilizing state feedback...
Dynamic multi-objective optimization (DMO) is one of the most challenging class of optimization problems where the objective functions change over time and the optimization algorithm is required to identify the corresponding Pareto optimal solutions with minimal time lag. DMO has received very little attention in the past and none of the existing multi-objective algorithms perform satisfactorily on...
This paper describes a model for visual homing. It uses Sarsa(lambda) as its learning algorithm, combined with the Jeffery divergence measure (JDM) as a way of terminating the task and augmenting the reward signal. The visual features are taken to be the histograms difference of the current view and the stored views of the goal location, taken for all RGB channels. A radial basis function layer acts...
Based on indications from the neuroscience and psychology, both perception and action can be internally simulated by activating sensor and motor areas in the brain without external sensory input or without any resulting overt behavior. This hypothesis, however, can be highly useful in the real robot applications. The robot, for instance, can cover some of the corrupted sensory inputs by replacing...
Autonomous robots must be able to learn and maintain models of their environments. In this context, the present work considers techniques for the classification and extraction of features from images in joined with artificial neural networks in order to use them in the system of mapping and localization of the mobile robot of Laboratory of Automation and Evolutive Computer (LACE). To do this, the...
In this paper, we propose a model to develop robotspsila covert and overt behaviors by using reinforcement and supervised learning jointly. The covert behaviors are handled by a motivational system, which is achieved through reinforcement learning. The overt behaviors are directly selected by imposing supervised signals. Instead of dealing with problems in controlled environments with a low-dimensional...
Ambiguity in sensory-motor signals from a mobile robot due mainly to noise and fluctuation makes a deterministic approach unsatisfactory. In this paper, a stochastic approach based-on Hidden Markov Models (HMMs) is proposed to recognize environment of a mobile robot. From this recognition a graph-based map is formed. Graph-based maps are important in decreasing memory and the computational cost. Two...
With the fast development of robotics and intelligent vehicles, there has been much research work on modeling and motion control of autonomous vehicles. However, due to model complexity, and unknown disturbances from dynamic environment, the motion control of autonomous vehicles is still a difficult problem. In this paper, a novel self-learning path-tracking control method is proposed for a car-like...
This work concerns practical issues surrounding the application of learning and memory in a real mobile robot towards optimal navigation in dynamic environments. A novel control system that contains two-level units (low-level and high-level) is developed and trained in a physical mobile robot ldquoe-Puckrdquo. In the low-level unit, the robotpsilas task is to navigate in a various local environments,...
We here introduce a novel adaptive controller for autonomous mobile robot that binds N types of sensory information. For each sensory modality, sensory-motor connection is made by a three-layered spiking neural network (SNN). The synaptic weights in the model have the property of spike timing-dependent plasticity (STDP) and regulated by presynaptic modulation signal from the sensory neurons. Each...
The paper proposes a real-time tracking algorithm for a moving object with mobile robot based on vision using adaptive color matching and Kalman filter. The adaptive color matching can limit the region containing moving object on vision image plane. It can adjust color matching threshold to reduce the influence of lighting variations in the scene. Kalman filter is used as our prediction module to...
The multi-robot task allocation (MRTA) especially in unknown complex environment is one of the fundamental problems, a mostly important object in research of multi-robot. The MRTA problem is initially formulated as a chance-constrained optimization problem. Monte Carlo simulation is used to verify the accuracy of the solution provided by the algorithm. Ant colony optimization (ACO) algorithm based...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.