Search results for "Robot"
showing 10 items of 1036 documents
An automatic system for humanoid dance creation
2016
Abstract The paper describes a novel approach to allow a robot to dance following musical rhythm. The proposed system generates a dance for a humanoid robot through the combination of basic movements synchronized with the music. The system made up of three parts: the extraction of features from audio file, estimation of movements through the Hidden Markov Models and, finally, the generation of dance. Starting from a set of given movements, the robot choices sequence of movements a suitable Hidden Markov Model, and synchronize them processing musical input. The proposed approach has the advantage that movement execution probabilities could be changed according evaluation of the dance executi…
A Fly-Inspired Mushroom Bodies Model for Sensory-Motor Control Through Sequence and Subsequence Learning
2016
Classification and sequence learning are relevant capabilities used by living beings to extract complex information from the environment for behavioral control. The insect world is full of examples where the presentation time of specific stimuli shapes the behavioral response. On the basis of previously developed neural models, inspired by Drosophila melanogaster, a new architecture for classification and sequence learning is here presented under the perspective of the Neural Reuse theory. Classification of relevant input stimuli is performed through resonant neurons, activated by the complex dynamics generated in a lattice of recurrent spiking neurons modeling the insect Mushroom Bodies n…
Sequence Learning in a Single Trial: A Spiking Neurons Model Based on Hippocampal Circuitry.
2020
ABSTRACTIn contrast with our everyday experience using brain circuits, it can take a prohibitively long time to train a computational system to produce the correct sequence of outputs in the presence of a series of inputs. This suggests that something important is missing in the way in which models are trying to reproduce basic cognitive functions. In this work, we introduce a new neuronal network architecture that is able to learn, in a single trial, an arbitrary long sequence of any known objects. The key point of the model is the explicit use of mechanisms and circuitry observed in the hippocampus, which allow the model to reach a level of efficiency and accuracy that, to the best of our…
A Cognitive Model of Trust for Biological and Artificial Humanoid Robots
2018
This paper presents a model of trust for biological and artificial humanoid robots and agents as antecedent condition of interaction. We discuss the cognitive engines of social perception that accounts for the units on which agents operate and the rules they follow when they bestow trust and assess trustworthiness. We propose that this structural information is the domain of the model. The model represents it in terms of modular cognitive structures connected by a parallel architecture. Finally we give a preliminary formalization of the model in the mathematical framework of the I/O automata for future computational and human-humanoid application.
Integrated dimensional and drive-train design optimization of a light-weight anthropomorphic arm
2012
An approach to minimize the mass of robotic manipulators is developed by integrated dimensional and drive-train optimization. The method addresses the influences of dimensions and characteristics of drive-trains in the design optimization. Constraints are formulated on the basis of kinematic performance and dynamic requirements, whereas the main objective is to minimize the total mass. Case studies are included to demonstrate the application of the optimization method in the design of assistive robots.
The absolute center of a unicyclic network
1989
Abstract A unicyclic network is one generalization of a tree network. In this paper we examine the problem of finding an absolute center of a unicyclic network. We show that this problem can be solved in linear time with respect to the number of vertices in the network.
Attitude stabilization control of a quadrotor UAV by using backstepping approach
2014
Published version of an article in the journal: Mathematical Problems in Engineering. Also available from the publisher at: http://dx.doi.org/10.1155/2014/749803 The modeling and attitude stabilization control problems of a four-rotor vertical takeoff and landing unmanned air vehicle (UAV) known as the quadrotor are investigated. The quadrotor's attitude is represented by the unit quaternion rather than Euler angles to avoid singularity problem. Taking dynamical behavior of motors into consideration and ignoring aerodynamic effect, a nonlinear controller is developed to stabilize the attitude. The control design is accomplished by using backstepping control technique. The proposed control l…
Kinematic calibration method for a 5-DOF Gantry-Tau parallel kinematic machine
2013
In this paper a new step-wise approach to kinematic calibration of a 5-DOF Gantry-Tau parallel kinematic machine (PKM) is presented. The approach can be adapted to the modular design of the PKM and the calibration could easily perform part of the assembly instructions for the machine. By using measurements from a laser tracker and least-squares estimates of polynomial functions, a typical accuracy of about 20 micrometer was achieved for the base actuators. The remaining set of 30 general parameters for the hexapod link structure and spherical joint connections were successfully estimated using the Complex search-based evolutionary algorithm.
Nonholonomic Interpolation for Kinematic Problems, Entropy and Complexity
2008
Here we present the main lines of a theory we developed in a series of previous papers, about the motion planning problem in robotics. We illustrate the theory with a few academic examples.
Graph-based algorithms for the efficient solution of a class of optimization problems
2018
In this paper, we address a class of specially structured problems that include speed planning, for mobile robots and robotic manipulators, and dynamic programming. We develop two new numerical procedures, that apply to the general case and to the linear subcase. With numerical experiments, we show that the proposed algorithms outperform generic commercial solvers.