Search results for "mot"
showing 10 items of 16577 documents
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…
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…
Towards the Design of Robotic Drivers for Full-Scale Self-Driving Racing Cars
2019
Autonomous vehicles are undergoing a rapid development thanks to advances in perception, planning and control methods and technologies achieved in the last two decades. Moreover, the lowering costs of sensors and computing platforms are attracting industrial entities, empowering the integration and development of innovative solutions for civilian use. Still, the development of autonomous racing cars has been confined mainly to laboratory studies and small to middle scale vehicles. This paper tackles the development of a planning and control framework for an electric full scale autonomous racing car, which is an absolute novelty in the literature, upon which we report our preliminary experim…
Autonomous Bearing Fault Diagnosis Method based on Envelope Spectrum
2017
Abstract Rolling element bearings are one of the fundamental components of a machine, and their failure is the most frequent cause of machine breakdown. Monitoring the bearing condition is vital to preventing unexpected shutdowns and improving their maintenance planning. Specifically, the bearing vibration can be measured and analyzed to diagnose bearing faults. Accurate fault diagnosis can be achieved by analyzing the envelope spectrum of a narrowband filtered vibration signal. The optimal narrow-band is centered at the resonance frequency of the bearing. However, how to determine the optimal narrow-band is a challenge. Several methods aim to identify the optimal narrow-band, but they are …
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.
Modeling of an active torsion bar automotive suspension for ride comfort and energy analysis in standard road profiles
2019
Abstract Chassis technology is evolving towards active suspension, in which actuators can provide forces to each wheel individually. This overcomes the traditional trade-off between comfort and handling, at the expense of increased complexity and electric consumption. To reduce power demand, regenerative solutions capable of harvesting a certain amount of energy otherwise dissipated in vehicle suspensions and to enhance vehicle dynamics for improving ride comfort and road safety at the same time have been researched. In this paper, an active suspension based on a torsion bar is modeled and analyzed under the excitation from standardized road profiles according to the ISO 8608 norm. A skyhoo…
Prediction of Vehicle Crashworthiness Parameters Using Piecewise Lumped Parameters and Finite Element Models
2018
Estimating the vehicle crashworthiness parameters experimentally is expensive and time consuming. For these reasons different modelling approaches are utilized to predict the vehicle behaviour and reduce the need for full-scale crash testing. The earlier numerical methods used for vehicle crashworthiness analysis were based on the use of lumped parameters models (LPM), a combination of masses and nonlinear springs interconnected in various configurations. Nowadays, the explicit nonlinear finite element analysis (FEA) is probably the most widely recognized modelling technique. Although informative, finite element models (FEM) of vehicle crash are expensive both in terms of man-hours put into…
Use of second-order sliding mode observer for low-accuracy sensing in hydraulic machines
2018
Low-accuracy sensing is very common for the large hydraulic machines and does not allow for directly measuring the relative velocity which can be, otherwise, required for the control and monitoring purposes. This paper provides a case study of designing the second-order sliding mode observer based on the super-twisting robust exact differentiator. The nominal part of the system dynamics is derived from the simple available system measurements and incorporated into the observer structure. Parasitic by-effects, arising from the sensor sampling, quantization, and non-modeled distortions due to mechanical sensor interface, are shown as the main causes of hampering the final (steady-state) conve…
Machine Learning Approaches for Activity Recognition and/or Activity Prediction in Locomotion Assistive Devices—A Systematic Review
2020
Locomotion assistive devices equipped with a microprocessor can potentially automatically adapt their behavior when the user is transitioning from one locomotion mode to another. Many developments in the field have come from machine learning driven controllers on locomotion assistive devices that recognize/predict the current locomotion mode or the upcoming one. This review synthesizes the machine learning algorithms designed to recognize or to predict a locomotion mode in order to automatically adapt the behavior of a locomotion assistive device. A systematic review was conducted on the Web of Science and MEDLINE databases (as well as in the retrieved papers) to identify articles published…
Internal model-based feedback control design for inversion-free feedforward rate-dependent hysteresis compensation of piezoelectric cantilever actuat…
2018
Abstract This study proposes a new rate-dependent feedforward compensator for compensation of hysteresis nonlinearities in smart materials-based actuators without considering the analytical inverse model. The proposed rate-dependent compensator is constructed with the inverse multiplicative structure of the rate-dependent Prandtl–Ishlinskii (RDPI) model. The study also presents an investigation for the compensation error when the proposed compensator is applied in an open-loop feedforward manner. Then, an internal model-based feedback control design is applied with the proposed feedforward compensator to a piezoelectric cantilever actuator. The experimental results illustrate that the propo…