Attitude and Position Estimation in UAVs using Artificial Landmarks and MEMS Sensors in a Virtual Environment

2020 ◽  
Author(s):  
Rafael Costa Fernandes ◽  
Paulo Sergio Silva ◽  
Felipe Ieda Fazanaro ◽  
Diego Paolo Ferruzzo Correa
Keyword(s):  
Computer Vision ◽  
Processing Time ◽  
Estimation Algorithm ◽  
Position Estimation ◽  
Simulation Software ◽  
Estimation Technique ◽  
Mems Sensors ◽  
Microelectromechanical System ◽  
Hybrid Estimation ◽  
The Cost

This work discusses the development of a hybrid estimation algorithm based on computer vision and microelectromechanical system sensors. A mathematical enviroment was developed to simulate the dynamics of the quadrotor and its sensors, a 3D simulation software was also developed, simulating a on-board camera. The results obtained were compared to a TRIAD/MEMS attitude and position estimation technique. A fourty times increase in precision was shown, at the cost of five times additional computational processing time.

scholarly journals FAST Pre-Filtering-Based Real Time Road Sign Detection for Low-Cost Vehicle Localization

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3590 ◽  
Author(s):  
Kyoungtaek Choi ◽  
Jae Kyu Suhr ◽  
Ho Gi Jung
Keyword(s):  
Embedded System ◽  
Processing Time ◽  
State Of The Art ◽  
Low Cost ◽  
Position Estimation ◽  
The State ◽  
Vehicle Localization ◽  
Localization System ◽  
Road Sign ◽  
The Cost

In order to overcome the limitations of GNSS/INS and to keep the cost affordable for mass-produced vehicles, a precise localization system fusing the estimated vehicle positions from low-cost GNSS/INS and low-cost perception sensors is being developed. For vehicle position estimation, a perception sensor detects a road facility and uses it as a landmark. For this localization system, this paper proposes a method to detect a road sign as a landmark using a monocular camera whose cost is relatively low compared to other perception sensors. Since the inside pattern and aspect ratio of a road sign are various, the proposed method is based on the part-based approach that detects corners and combines them to detect a road sign. While the recall, precision, and processing time of the state of the art detector based on a convolutional neural network are 99.63%, 98.16%, and 4802 ms respectively, the recall, precision, and processing time of the proposed method are 97.48%, 98.78%, and 66.7 ms, respectively. The detection performance of the proposed method is as good as that of the state of the art detector and its processing time is drastically reduced to be applicable for an embedded system.

Perancangan dan Pembuatan Alat Bantu Meja Putar untuk Mesin Cnc 4 Axis

2016 ◽  
Vol 10 (2) ◽  
pp. 162-171
Author(s):  
Hafid Hafid ◽  
Tatang Sutisna
Keyword(s):  
Processing Time ◽  
Rotary Table ◽  
Engineering Process ◽  
Cnc Machine ◽  
Economical Analysis ◽  
Machining Center ◽  
Design And Manufacturing ◽  
The Cost ◽  
Productivity And Competitiveness

The design and manufacturing of the rotary table with the specification Ø 170 mm (6 inches) for CNC machine 4 axis has been done. The objective of manufacturing a rotary table is to increase the efficiency of CNC machine Hardford 4 axis to be above 80% in line machining center CV. IM’s workshop. The engineering methods was taken, consist of: working preparation, manufacturing of working drawing, engineering process, the manufacturing and testing. The prototype has been tested and operated, the resulting of increasing productivity of which were as follows: the process of assembling was increased to be 3 time ( before 1 time) and processing time for a specific case reduced from 5 hours to 3 hours, number of operators for the case of assembling the rotary reduced to 1 person (before 4 persons), safety and security become to be better. The results show increased efficiency of CNC machine Hardford, from under 50% to be above 80%. Based on the economical analysis obtained by the cost of good sold (C.G.S) of the rotary table is IDR 34.060.000. The results presented in this paper is expected to be case study for developing a business of the metal and engineering SMEs domestic to the effort of improving efficiency, quality, productivity and competitiveness in global market.ABSTRAKPerancangan dan pembuatan alat bantu meja putar (rotary table) dengan spesifikasi teknis Ø 170 mm (6 inci) untuk mesin CNC 4 axis telah dilakukan. Tujuan pembuatan rotary table adalah untuk meningkatkan efisiensi mesin CNC Hardford 4 axis di atas 80% pada line machining center Bengkel CV. IM. Metode rancang bangun yang dilakukan, meliputi: persiapan kerja, pembuatan gambar kerja, proses engineering, pembuatan dan uji coba. Prototip tersebut telah diuji coba dan dioperasikan dengan hasil peningkatan produktivitas sebagai berikut: proses pengerjaan bongkar pasang meningkat menjadi 3 kali (sebelumnya 1 kali) dan waktu pengerjaan untuk kasus tertentu berkurang dari 5 jam menjadi 3 jam, jumlah operator untuk kasus bongkar pasang rotary berkurang menjadi 1 orang (sebelumnya 4 orang), keselamatan kerja dan keamanan menjadi lebih baik. Hasil peningkatan berupa efisiensi mesin CNC Hardford 4 axis dari sebelumnya di bawah 50% menjadi di atas 80%. Berdasarkan hasil perhitungan analisis ekonomi diperoleh harga pokok produksi (HPP) alat bantu meja putar adalah sebesar Rp. 34.060.000. Bahasan ini diharapkan menjadi contoh kasus bagi pengembangan usaha IKM logam dan mesin dalam negeri untuk meningkatkan efisiensi, mutu, produktivitas dan keunggulan daya saing di pasar global.Kata kunci: alat bantu meja putar, mesin CNC, harga pokok produksi

scholarly journals A Survey on Contrastive Self-Supervised Learning

Technologies ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 2
Author(s):  
Ashish Jaiswal ◽  
Ashwin Ramesh Babu ◽  
Mohammad Zaki Zadeh ◽  
Debapriya Banerjee ◽  
Fillia Makedon
Keyword(s):  
Computer Vision ◽  
Supervised Learning ◽  
Language Processing ◽  
Large Scale ◽  
Performance Comparison ◽  
Extensive Review ◽  
Future Directions ◽  
Dominant Component ◽  
Supervised Methods ◽  
The Cost

Self-supervised learning has gained popularity because of its ability to avoid the cost of annotating large-scale datasets. It is capable of adopting self-defined pseudolabels as supervision and use the learned representations for several downstream tasks. Specifically, contrastive learning has recently become a dominant component in self-supervised learning for computer vision, natural language processing (NLP), and other domains. It aims at embedding augmented versions of the same sample close to each other while trying to push away embeddings from different samples. This paper provides an extensive review of self-supervised methods that follow the contrastive approach. The work explains commonly used pretext tasks in a contrastive learning setup, followed by different architectures that have been proposed so far. Next, we present a performance comparison of different methods for multiple downstream tasks such as image classification, object detection, and action recognition. Finally, we conclude with the limitations of the current methods and the need for further techniques and future directions to make meaningful progress.

scholarly journals Exergy Assessment and Thermo-Economic Analysis of Hybrid Solar Systems with Seasonal Storage and Heat Pump Coupling in the Social Housing Sector in Zaragoza

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1279
Author(s):  
Amaya Martínez-Gracia ◽  
Sergio Usón ◽  
Mª Teresa Pintanel ◽  
Javier Uche ◽  
Ángel A. Bayod-Rújula ◽  
...  
Keyword(s):  
Heat Pump ◽  
Social Housing ◽  
Energy System ◽  
Simulation Software ◽  
Solar Panels ◽  
Solar Systems ◽  
Under Construction ◽  
The Cost ◽  
Solar Resource ◽  
Solar Field

A real case study of an energy system based on a Solar Assisted Heat Pump (SAHP) fed by hybrid photovoltaic-thermal solar panels (PVT) and seasonal storage (SS) is presented in this paper. Exergy and exergy cost analyses are proposed as complementary methods for the assessment and better understanding of the efficiency of this cogeneration solar configuration. The system performance takes advantage of storage heat in summer, when the solar resource is high in Spain, and is then later consumed during the cold winter (heating season). The building is devoted to social housing, and it is currently under construction. The assessment is based on simulations developed using TRNSYS, a dynamic simulation software for energy systems. Results show that the unit exergy cost of the solar field is around 6. The cost of the seasonal storage is higher, about 13, and its formation is affected both by its own irreversibility and by the irreversibility of the PVT solar field. The cost of the heat delivered by the heat pump is around 15, being affected by all the upstream units and even by the grid. Besides, the analysis points out strategies for improving the system efficiency, such as increasing the size of the storage tank or improving the control strategy of the boiler.

Based on Numerical Simulation of High-Performance Parallel Machine Muffler Experimental Calibration

2013 ◽  
Vol 718-720 ◽  
pp. 1645-1650
Author(s):  
Gen Yin Cheng ◽  
Sheng Chen Yu ◽  
Zhi Yong Wei ◽  
Shao Jie Chen ◽  
You Cheng
Keyword(s):  
Numerical Simulation ◽  
Finite Element ◽  
Boundary Element ◽  
Message Passing ◽  
High Performance ◽  
Message Passing Interface ◽  
Parallel Machine ◽  
Simulation Software ◽  
Experimental Calibration ◽  
The Cost

Commonly used commercial simulation software SYSNOISE and ANSYS is run on a single machine (can not directly run on parallel machine) when use the finite element and boundary element to simulate muffler effect, and it will take more than ten days, sometimes even twenty days to work out an exact solution as the large amount of numerical simulation. Use a high performance parallel machine which was built by 32 commercial computers and transform the finite element and boundary element simulation software into a program that can running under the MPI (message passing interface) parallel environment in order to reduce the cost of numerical simulation. The relevant data worked out from the simulation experiment demonstrate that the result effect of the numerical simulation is well. And the computing speed of the high performance parallel machine is 25 ~ 30 times a microcomputer.

A weak derivative approach to optimization of threshold parameters in a multicomponent maintenance system

2001 ◽  
Vol 38 (02) ◽  
pp. 386-406 ◽  
Author(s):  
Bernd Heidergott
Keyword(s):  
Optimization Problems ◽  
Estimation Algorithm ◽  
Replacement Policy ◽  
Cost Performance ◽  
Weak Derivative ◽  
Preventive Replacement ◽  
Maintenance System ◽  
Threshold Optimization ◽  
Age Replacement ◽  
The Cost

We consider a multicomponent maintenance system controlled by an age replacement policy: when one of the components fails, it is immediately replaced; all components older than a threshold age θ are preventively replaced. Costs are associated with each maintenance action, such as replacement after failure or preventive replacement. We derive a weak derivative estimator for the derivative of the cost performance with respect to θ. The technique is quite general and can be applied to many other threshold optimization problems in maintenance. The estimator is easy to implement and considerably increases the efficiency of a Robbins-Monro type of stochastic approximation algorithm. The paper is self-contained in the sense that it includes a proof of the correctness of the weak derivative estimation algorithm.

scholarly journals A DCM Based Attitude Estimation Algorithm for Low-Cost MEMS IMUs

2015 ◽  
Vol 2015 ◽  
pp. 1-18 ◽  
Author(s):  
Heikki Hyyti ◽  
Arto Visala
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Low Cost ◽  
Direction Cosine ◽  
Estimation Algorithm ◽  
Calibration Method ◽  
Attitude Estimation ◽  
Mems Sensors ◽  
Acceleration Sensors ◽  
Adaptive Extended Kalman Filter

An attitude estimation algorithm is developed using an adaptive extended Kalman filter for low-cost microelectromechanical-system (MEMS) triaxial accelerometers and gyroscopes, that is, inertial measurement units (IMUs). Although these MEMS sensors are relatively cheap, they give more inaccurate measurements than conventional high-quality gyroscopes and accelerometers. To be able to use these low-cost MEMS sensors with precision in all situations, a novel attitude estimation algorithm is proposed for fusing triaxial gyroscope and accelerometer measurements. An extended Kalman filter is implemented to estimate attitude in direction cosine matrix (DCM) formation and to calibrate gyroscope biases online. We use a variable measurement covariance for acceleration measurements to ensure robustness against temporary nongravitational accelerations, which usually induce errors when estimating attitude with ordinary algorithms. The proposed algorithm enables accurate gyroscope online calibration by using only a triaxial gyroscope and accelerometer. It outperforms comparable state-of-the-art algorithms in those cases when there are either biases in the gyroscope measurements or large temporary nongravitational accelerations present. A low-cost, temperature-based calibration method is also discussed for initially calibrating gyroscope and acceleration sensors. An open source implementation of the algorithm is also available.

scholarly journals Best-first Enumeration Based on Bounding Conflicts, and its Application to Large-scale Hybrid Estimation (Extended Abstract)

2020 ◽  
Author(s):  
Eric Timmons ◽  
Brian C. Williams
Keyword(s):  
Large Scale ◽  
Search Space ◽  
Estimation Methods ◽  
Directed Search ◽  
Hybrid Estimation ◽  
Continuous State ◽  
Order Of Magnitude ◽  
State Models ◽  
The Cost ◽  
Belief States

State estimation methods based on hybrid discrete and continuous state models have emerged as a method of precisely computing belief states for real world systems, however they have difficulty scaling to systems with more than a handful of components. Classical, consistency based diagnosis methods scale to this level by combining best-first enumeration and conflict-directed search. While best-first methods have been developed for hybrid estimation, conflict-directed methods have thus far been elusive as conflicts summarize constraint violations, but probabilistic hybrid estimation is relatively unconstrained. In this paper we present an approach (A*BC) that unifies best-first enumeration and conflict-directed search in relatively unconstrained problems through the concept of "bounding" conflicts, an extension of conflicts that represent tighter bounds on the cost of regions of the search space. Experiments show that an A*BC powered state estimator produces estimates up to an order of magnitude faster than the current state of the art, particularly on large systems.

Sign in / Sign up

Export Citation Format

Share Document