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This paper presents a simplified primal-dual neural network based on linear variational inequalities (LVI) for online repetitive motion planning of PA10 robot manipulator. To do this, a drift-free criterion is exploited in the form of a quadratic function. In addition, the repetitive-motion-planning scheme could incorporate the joint limits and joint velocity limits simultaneously. Such a scheme is...
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 paper studies the use of neural networks in robotic position/orientation control. The process is divided into two tasks, i.e., the inverse kinematics solution and the adaptive motor control. Simulation results of a three-link robotic arm in a two-dimensional workspace demonstrate the validity of the design. The hierarchal nature of the design allows it to be applied to more complicated systems...
Exploratory activities seem to be crucial for our cognitive development. According to psychologists, exploration is an intrinsically rewarding behaviour. The developmental robotics aims to design computational systems that are endowed with such an intrinsic motivation mechanism. There are possible links between developmental robotics and machine learning. Affective computing takes into account emotions...
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...
Since machine learning has become a tool to make more efficient design of sophisticated systems, we present in this paper a novel methodology to create powerful neural network controllers for complex systems while minimising the design effort. Using a robot task as a case study, we have shown that using the feedback from the robot itself, the system can learn from experience, or example provided by...
Semantic scene classification, robotic state recognition, and many other real-world applications involve multi-label classification with imbalanced data. In this paper, we address these problems by using an enrichment process in neural net training. The enrichment process can manage the imbalanced data and train the neural net with high classification accuracy. Experimental results on a robotic arm...
This paper deals with visual-motor coordination of a 7 dof robot manipulator for pick and place applications. Three issues are dealt with in this paper - finding a feasible inverse kinematic solution without using any orientation information, resolving redundancy at position level and finally maintaining the fidelity of information during clustering process thereby increasing accuracy of inverse kinematic...
Path planning of air robot is a complicated global optimum problem. Intelligent water drops (IWD) algorithm is newly presented under the inspiration of the dynamic of river systems and the actions that water drops do in the rivers, and it is easy to combine with other methods in optimization. In this paper, we propose an improved IWD optimization algorithm for solving the air robot path planning problems...
Sociable robots are embodied agents that are part of a heterogeneous society of robots and humans. They are able to recognize human beings and each other, and engage in social interactions. The use of a robotic architecture may strongly reduce the time and effort required to construct a sociable robot. However, a robotic architecture for sociable robots must have structures and mechanisms to allow...
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...
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...
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...
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...
A novel wake-sleep learning architecture for processing a robotpsilas facial expressions is introduced. According to neuroscience evidence, associative learning of emotional responses and facial expressions occurs in the brain in the amygdala. Here we propose an architecture inspired by how the amygdala receives information from other areas of the brain to discriminate it and generate innate responses...
Segmentation of the surgeonpsilas hand movements during the surgery into more primitive parts and recognition of those parts using Kohonen map is discussed in present paper. Main advantages of the proposed approach are that it allows to take into account dynamical characteristics of the hand movements and exclude probability of human error in building etalon segmentation. Ability to recognize current...
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...
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...
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...
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...
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