Search results for "2020"
showing 10 items of 4977 documents
Compensation of Nonlinear Torsion in Flexible Joint Robots: Comparison of Two Approaches
2015
Flexible joint robots, in particularly those which are equipped with harmonic-drive gears, can feature elasticities with hysteresis. Under heavy loads and large joint torques the hysteresis lost motion can lead to significant errors of tracking and positioning of the robotic links. In this paper, two approaches for compensating the nonlinear joint torsion with hysteresis are described and compared with each other. Both methods assume the measured signals available only on the motor side of joint transmissions. The first approach assumes a rigid-link manipulator model and transforms the desired link trajectory into that of the motor drives by using the inverse dynamics and inverse hysteresis…
Adding Active Damping to Energy-Efficient Electro-Hydraulic Systems for Robotic Manipulators — Comparing Pressure and Acceleration Feedback
2020
The growing interest in energy efficiency, plug-and-play commissioning, and reduced maintenance for heavy-duty robotic manipulators directs towards self-contained, electro-hydraulic cylinders. These drives are characterized by extremely low damping that causes unwanted oscillations of the mechanical structure. Adding active damping to this class of energy-efficient architectures is essential. Hence, this paper bridges a literature gap by presenting a systematic comparison grounded on a model-based tuning of both pressure and acceleration feedback. It is shown that both approaches increase the system damping hugely and improve the performance of the linear system. Acceleration feedback shoul…
Extreme minimal learning machine: Ridge regression with distance-based basis
2019
The extreme learning machine (ELM) and the minimal learning machine (MLM) are nonlinear and scalable machine learning techniques with a randomly generated basis. Both techniques start with a step in which a matrix of weights for the linear combination of the basis is recovered. In the MLM, the feature mapping in this step corresponds to distance calculations between the training data and a set of reference points, whereas in the ELM, a transformation using a radial or sigmoidal activation function is commonly used. Computation of the model output, for prediction or classification purposes, is straightforward with the ELM after the first step. In the original MLM, one needs to solve an addit…
Vision based attitude and altitude estimation for UAVs in dark environments
2011
This paper presents a system dedicated to the real-time estimation of attitude and altitude for unmanned aerial vehicles (UAV) under low light and dark environment. This system consists in a fisheye camera, which allows to cover a large field of view (FOV), and a laser circle projector mounted on a fixed baseline. The approach, close to structured light systems, uses the geometrical information obtained by the projection of the laser circle onto the ground plane and perceived by the camera. We present a theoretical study of the system in which the camera is modelled as a sphere and show that the estimation of a conic on this sphere allows to obtain the attitude and the altitude of the robot…
Omnidirectional vision for UAV: applications to attitude, motion and altitude estimation for day and night conditions
2012
International audience; This paper presents the combined applications of omnidirectional vision featuring on its application to aerial robotics. Omnidirectional vision is first used to compute the attitude, altitude and motion not only in rural environment but also in the urban space. Secondly, a combination of omnidirectional and perspective cameras permits to estimate the altitude. Finally we present a stereo system consisting of an omnidirectional camera with a laser pattern projector enables to calculate the altitude and attitude during the improperly illuminated conditions to dark environments. We demonstrate that omnidirectional camera in conjunction with other sensors is suitable cho…
Accelerated bearing life-Time test rig development for low speed data acquisition
2017
Condition monitoring plays an important role in rotating machinery to ensure reliability of the equipment, and to detect fault conditions at an early stage. Although health monitoring methodologies have been thoroughly developed for rotating machinery, low-speed conditions often pose a challenge due to the low signal-to-noise ratio. To this aim, sophisticated algorithms that reduce noise and highlight the bearing faults are necessary to accurately diagnose machines undergoing this condition. In the development phase, sensor data from a healthy and damaged bearing rotating at low-speed is required to verify the performance of such algorithms. A test rig for performing accelerated life-time t…
Adaptive Consensus-Based Distributed Kalman Filter for WSNs with Random Link Failures
2016
Wireless Sensor Networks have emerged as a very powerful tool for the monitoring and control, over large areas, of diverse phenomena. One of the most appealing properties of these networks is their potentiality to perform complex tasks in a total distributed fashion, without requiring a central entity. In this scenario, where nodes are constrained to use only local information and communicate with one-hop neighbors, iterative consensus algorithms are extensively used due to their simplicity. In this work, we propose the design of a consensus-based distributed Kalman filter for state estimation, in a sensor network whose connections are subject to random failures. As a result of this unrelia…
Topology design to increase network lifetime in WSN for graph filtering in consensus processes
2018
Graph filters, which are considered as the workhorses of graph signal analysis in the emerging field of signal processing on graphs, are useful for many applications such as distributed estimation in wireless sensor networks. Many of these tasks are based on basic distributed operators such as consensus, which are carried out by sensor devices under limited energy supply. To cope with the energy constraints, this paper focuses on designing the network topology in order to maximize the network lifetime and reduce the energy consumption when applying graph filters. The problem is a complex combinatorial problem and in this work, we propose two efficient heuristic algorithms for solving it. We…
BIAM: a new bio-inspired analysis methodology for digital ecosystems based on a scale-free architecture
2017
Today we live in a world of digital objects and digital technology; industry and humanities as well as technologies are truly in the midst of a digital environment driven by ICT and cyber informatics. A digital ecosystem can be defined as a digital environment populated by interacting and competing digital species. Digital species have autonomous, proactive and adaptive behaviors, regulated by peer-to-peer interactions without central control point. An interconnecting architecture with few highly connected nodes (hubs) and many low connected nodes has a scale- free architecture. A new bio-inspired analysis methodology (BIAM) environment, an investigation strategy for information flow, fault…
On Stability of Virtual Torsion Sensor for Control of Flexible Robotic Joints with Hysteresis
2019
Author's accepted manuscript (postprint). This article has been published in a revised form in Robotica, http://doi.org/10.1017/S0263574719001358. This version is free to view and download for private research and study only. Not for re-distribution or re-use. © 2019 Cambridge University Press. Available from 25/03/2020. Aim of the virtual torsion sensor (VTS) is in observing the nonlinear deflection in the flexible joints of robotic manipulators and, by its use, improving positioning control of the joint load. This model-based approach utilizes the motor-side sensing only and, therefore, replaces the load-side encoders at nearly zero hardware costs. For being applied in the closed control …