Search results for " artificial intelligence"
showing 10 items of 1992 documents
A Geometrical Approach for Vision Based Attitude and Altitude Estimation for UAVs in Dark Environments
2012
International audience; This paper presents a single camera and laser system dedicated to the realtime estimation of attitude and altitude for unmanned aerial vehicles (UAV) under low illumination conditions to dark environments. The fisheye camera allows to cover a large field of view (FOV). The approach, close to structured light systems, uses the geometrical information obtained by the projection of a laser circle onto the ground plane and perceived by the camera. We propose some experiments based on simulated data and real sequences. The results show good agreement with the ground truth values from the commercial sensors in terms of its accuracy and correctness. The results also prove i…
Method for 3D fibre reconstruction on a microrobotic platform
2015
Automated handling of a natural fibrous object requires a method for acquiring the three-dimensional geometry of the object, because its dimensions cannot be known beforehand. This paper presents a method for calculating the three-dimensional reconstruction of a paper fibre on a microrobotic platform that contains two microscope cameras. The method is based on detecting curvature changes in the fibre centreline, and using them as the corresponding points between the different views of the images. We test the developed method with four fibre samples and compare the results with the references measured with an X-ray microtomography device. We rotate the samples through 16 different orientatio…
Direct Torque Control of a Small Wind Turbine with a Sliding-Mode Speed Controller
2016
In this paper. the method of direct torque control in the presence of a sliding-mode speed controller is proposed for a small wind turbine being used in water heating applications. This concept and control system design can be expanded to grid connected or off-grid applications. Direct torque control of electrical machines has shown several advantages including very fast dynamics torque control over field-oriented control. Moreover. the torque and flux controllers in the direct torque control algorithms are based on hvsteretic controllers which are nonlinear. In the presence of a sliding-mode speed control. a nonlinear control system can be constructed which is matched for AC/DC conversion …
Online fitted policy iteration based on extreme learning machines
2016
Reinforcement learning (RL) is a learning paradigm that can be useful in a wide variety of real-world applications. However, its applicability to complex problems remains problematic due to different causes. Particularly important among these are the high quantity of data required by the agent to learn useful policies and the poor scalability to high-dimensional problems due to the use of local approximators. This paper presents a novel RL algorithm, called online fitted policy iteration (OFPI), that steps forward in both directions. OFPI is based on a semi-batch scheme that increases the convergence speed by reusing data and enables the use of global approximators by reformulating the valu…
A theoretical framework for product relationships description over space and time in integrated design
2016
ABSTRACTThis paper presents a novel qualitative description theory in the context of integrated design, which here incorporates assembly sequence planning in the early product design stages (also called assembly oriented design – AOD). Based on a literature review of current AOD approaches, product models and mereotopology-based theories, the authors introduce a promising mereotopological theory which enables the formal product relationships description in integrated design by introducing an emerging framework, four-dimensionalism (i.e. perdurantism in philosophy). The proposed efforts aim at providing a concrete basis for describing the evolution of spatial entities (i.e. product parts) an…
Regenerative scheduling problem in engineer to order manufacturing: an economic assessment
2021
The dynamic production scheduling is a very complex process that may arise from the occurrence of unpredictable situations such as the arrival of new orders besides the ones already accepted. As a consequence, companies may often encounter several difficulties to make decisions about the new orders acceptance and sequencing along with the production of the existing ones. With this recognition, a mathematical programming model for the regenerative scheduling problem with deterministic processing times is formulated in the present paper to evaluate the economic advantage of accepting a new order in an engineer to order (ETO) manufacturing organization. The real case of an Italian ETO company …
K-nearest neighbor driving active contours to delineate biological tumor volumes
2019
Abstract An algorithm for tumor delineation in positron emission tomography (PET) is presented. Segmentation is achieved by a local active contour algorithm, integrated and optimized with the k-nearest neighbor (KNN) classification method, which takes advantage of the stratified k-fold cross-validation strategy. The proposed approach is evaluated considering the delineation of cancers located in different body districts (i.e. brain, head and neck, and lung), and considering different PET radioactive tracers. Data are pre-processed in order to be expressed in terms of standardized uptake value, the most widely used PET quantification index. The algorithm uses an initial, operator selected re…
Patented intelligence: Cloning human decision models for Industry 4.0
2018
Industry 4.0 is a trend related to smart factories, which are cyber-physical spaces populated and controlled by the collective intelligence for the autonomous and highly flexible manufacturing purposes. Artificial Intelligence (AI) embedded into various planning, production, and management processes in Industry 4.0 must take the initiative and responsibility for making necessary real-time decisions in many cases. In this paper, we suggest the Pi-Mind technology as a compromise between completely human-expert-driven decision-making and AI-driven decision-making. Pi-Mind enables capturing, cloning and patenting essential parameters of the decision models from a particular human expert making …
Fault detection for nonlinear networked systems based on quantization and dropout compensation: An interval type-2 fuzzy-model method
2016
Abstract This paper investigates the problem of filter-based fault detection for a class of nonlinear networked systems subject to parameter uncertainties in the framework of the interval type-2 (IT2) T–S fuzzy model-based approach. The Bernoulli random distribution process and logarithm quantizer are used to describe the measurement loss and signals quantization, respectively. In the framework of the IT2 T–S fuzzy model, the parameter uncertainty is handled by the membership functions with lower and upper bounds. A novel IT2 fault detection filter is designed to guarantee the residual system to be stochastically stable and satisfy the predefined H ∞ performance. It should be mentioned that…
George-Veeramani Fuzzy Metrics Revised
2018
In this note, we present an alternative approach to the concept of a fuzzy metric, calling it a revised fuzzy metric. In contrast to the traditional approach to the theory of fuzzy metric spaces which is based on the use of a t-norm, we proceed from a t-conorm in the definition of a revised fuzzy metric. Here, we restrict our study to the case of fuzzy metrics as they are defined by George-Veeramani, however, similar revision can be done also for some other approaches to the concept of a fuzzy metric.