Search results for " IMAGE"
showing 10 items of 3936 documents
Comparison of Model-Based Simultaneous Position and Stiffness Control Techniques for Pneumatic Soft Robots
2020
Soft robots have been extensively studied for their ability to provide both good performance and safe human-robot interaction. In this paper, we present and compare the performance of two model-based control techniques with the common aim to independently and simultaneously control position and stiffness of a pneumatic soft robot’s joint. The dynamic system of a robot arm with flexible joints actuated by a pneumatic antagonistic pair of actuators, so-called McKibben artificial muscles, will be regarded, while its dynamic parameters will be considered imprecise. Simulation results are provided to verify the performance of the algorithms.
Adaptive Control of Quantized Uncertain Nonlinear Systems
2017
Abstract This paper proposes a new adaptive controller for uncertain nonlinear systems in presence of quantized input signal and unknown external disturbance. A hysteresis quantizer is incorporated to reduce chattering phenomenon. By proposing a new transformation of the final control signal, using the sector-bound property of the quantizer and introducing a hyperbolic tangent function, the effects from input quantization and external disturbance are effectively compensated and the Lipschitz condition required for the nonlinear functions in the systems is removed. Besides showing global stability, tracking error performance is also established and can be adjusted by tuning certain design pa…
Making Industrial Robots Smarter with Adaptive Reasoning and Autonomous Thinking for Real-Time Tasks in Dynamic Environments: A Case Study
2018
In order to extend the abilities of current robots in industrial applications towards more autonomous and flexible manufacturing, this work presents an integrated system comprising real-time sensing, path-planning and control of industrial robots to provide them with adaptive reasoning, autonomous thinking and environment interaction under dynamic and challenging conditions. The developed system consists of an intelligent motion planner for a 6 degrees-of-freedom robotic manipulator, which performs pick-and-place tasks according to an optimized path computed in real-time while avoiding a moving obstacle in the workspace. This moving obstacle is tracked by a sensing strategy based on ma-chin…
Advances in Practical Applications of Agents, Multi-Agent Systems, and Sustainability: The PAAMS Collection
2015
This volume presents the papers that have been accepted for the 2015 special sessions of the 13th International Conference on Practical Applications of Agents and Multi-Agent Systems, held at University of Salamanca, Spain, at 3rd-5th June, 2015: Agents Behaviours and Artificial Markets (ABAM); Agents and Mobile Devices (AM); Multi-Agent Systems and Ambient Intelligence (MASMAI); Web Mining and Recommender systems (WebMiRes); Learning, Agents and Formal Languages (LAFLang); Agent-based Modeling of Sustainable Behavior and Green Economies (AMSBGE); Emotional Software Agents (SSESA) and Intelligent Educational Systems (SSIES). The volume also includes the paper accepted for the Doctoral Conso…
Adaptive Robot Control – An Experimental Comparison
2012
This paper deals with experimental comparison between stable adaptive controllers of robotic manipulators based on Model Based Adaptive, Neural Network and Wavelet -Based control. The above control methods were compared with each other in terms of computational efficiency, need for accurate mathematical model of the manipulator and tracking performances. An original management algorithm of the Wavelet Network control scheme has been designed, with the aim of constructing the net automatically during the trajectory tracking, without the need to tune it to the trajectory itself. Experimental tests, carried out on a planar two link manipulator, show that the Wavelet-Based control scheme, with…
Surrogate models for the compressive strength mapping of cement mortar materials
2021
Despite the extensive use of mortar materials in constructions over the last decades, there is not yet a robust quantitative method available in the literature, which can reliably predict their strength based on the mix components. This limitation is attributed to the highly nonlinear relation between the mortar’s compressive strength and the mixed components. In this paper, the application of artificial intelligence techniques for predicting the compressive strength of mortars is investigated. Specifically, Levenberg–Marquardt, biogeography-based optimization, and invasive weed optimization algorithms are used for this purpose (based on experimental data available in the literature). The c…
Traffic data acquirement by unmanned aerial vehicle
2017
This paper presents a methodology aimed to acquire traffic flow data through the employment of unmanned aerial vehicles (UAVs). The study is focused on the determination of driving behavior parameters of road users and on the reconstruction of traffic flow Origin/Destination matrix. The methodology integrates UAV flights with video image processing technique, and the capability of geographic information systems, to represent spatiotemporal phenomena. In particular, analyzing different intersections, the attention of the authors is focused on users’ gap acceptance in a naturalistic drivers’ behavior condition (drivers are not influenced by the presence of instruments and operators on the roa…
Rotation estimation and vanishing point extraction by omnidirectional vision in urban environment
2012
International audience; Rotation estimation is a fundamental step for various robotic applications such as automatic control of ground/aerial vehicles, motion estimation and 3D reconstruction. However it is now well established that traditional navigation equipments, such as global positioning systems (GPSs) or inertial measurement units (IMUs), suffer from several disadvantages. Hence, some vision-based works have been proposed recently. Whereas interesting results can be obtained, the existing methods have non-negligible limitations such as a difficult feature matching (e.g. repeated textures, blur or illumination changes) and a high computational cost (e.g. analyze in the frequency domai…
Multi-Component Fault Detection in Wind Turbine Pitch Systems Using Extended Park's Vector and Deep Autoencoder Feature Learning
2018
Pitch systems are among the wind turbine components with most frequent failures. This article presents a multicomponent fault detection for induction motors and planetary gearboxes of the electric pitch drives using only the three-phase motor line currents. A deep autoencoder is used to extract features from the extended Park's vector modulus of the motor three-phase currents and a support vector machine to classify faults. The methodology is validated in a laboratory setup of a scaled pitch drive, with four commonly occurring faults, namely, the motor stator turns fault, broken rotor bars fault, planetary gearbox bearing fault and planet gear faults, under varying load and speed conditions.
Ant Colony Optimisation-Based Classification Using Two-Dimensional Polygons
2016
The application of Ant Colony Optimization to the field of classification has mostly been limited to hybrid approaches which attempt at boosting the performance of existing classifiers (such as Decision Trees and Support Vector Machines (SVM)) — often through guided feature reductions or parameter optimizations.