Search results for "Biotechnology"
showing 10 items of 5678 documents
Summarizing Large Scale 3D Mesh
2018
International audience; Recent progress in 3D sensor devices and in semantic mapping allows to build very rich HD 3D maps very useful for autonomous navigation and localization. However , these maps are particularly huge and require important memory capabilities as well computational resources. In this paper, we propose a new method for summarizing a 3D map (Mesh) as a set of compact spheres in order to facilitate its use by systems with limited resources (smartphones, robots, UAVs, ...). This vision-based summarizing process is applied in a fully automatic way using jointly photometric, geometric and semantic information of the studied environment. The main contribution of this research is…
Model-Free Sliding-Mode-Based Detection and Estimation of Backlash in Drives With Single Encoder
2021
Backlash is a frequently encountered problem for various drives, especially those equipped with a single encoder onside of the controlled actuator. This brief proposes a sliding-mode differentiator-based estimation of unknown backlash size while measuring the actuator displacement only. Neither actuator nor load dynamics are explicitly known, while a principal second-order actuator behavior is assumed. We make use of the different perturbation dynamics distinctive for different backlash modes and an unbounded impulse-type perturbation at impact. The latter leads to transient loss of the sliding-mode and allows for detecting an isolated time instant of the backlash occurrence. The proposed m…
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…
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…
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…
Cross-correlation of whitened vibration signals for low-speed bearing diagnostics
2019
Abstract Rolling-element bearings are crucial components in all rotating machinery, and their failure will initially degrade the machine performance, and later cause complete shutdown. The period between an initial crack and complete failure is short due to crack propagation. Therefore, early fault detection is important to avoid unexpected machine shutdown and to aid in maintenance scheduling. Bearing condition monitoring has been applied for several decades to detect incipient faults at an early stage. However, low-speed conditions pose a challenge for bearing fault diagnosis due to low fault impact energy. To reliably detect bearing faults at an early stage, a new method termed Whitened …
Re-forming end-of-life components through single point incremental forming
2020
Abstract Applying Circular Economy strategies is mandatory to face material demand while minimizing the environmental impact. Manufacturing processes are to be thought as means to enable material/component reuse strategies. This paper presents the suitability of Single Point Incremental Forming (SPIF) to re-form End-of-life sheet metal components. Deep drawing followed by SPIF process on aluminium alloys were carried out to simulate reforming processes chain. The resulting thinning and strain distributions were experimentally analysed for different configurations. The research proves that the local action and enhanced formability nature of SPIF allow non-homogeneously thinned and reduced fo…
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…
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…