scholarly journals Recovering Walking Trajectories from Local Measurements and Inertia Data

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Lifeng Zhu ◽  
Chenghao Xu ◽  
Ke Shi ◽  
Wei Li ◽  
Aiguo Song ◽  
...  
Keyword(s):  
Optimization Problems ◽  
Location Based Services ◽  
Small Scale ◽  
Outdoor Setting ◽  
Walking Motion ◽  
Optical Motion ◽  
Local Measurements ◽  
Optical Motion Capture ◽  
Scale Optimization

Capturing walking trajectories is useful for motion planning and various location-based services. Traditionally, it is a challenging task because it is expensive to install infrastructures, especially in an outdoor setting. As another choice, the reconstructed walking trajectories suffer from the drifting problem from captured inertia data. In this work, we study the biped walking motion and propose a method to recover walking trajectories by introducing local measurements between the feet to the system, in combination with the orientation from inertia data. We design a few local measurements which can be passively captured. After analyzing these measurements, the walking trajectory is progressively recovered by solving a set of small-scale optimization problems. By comparing with the trajectories extracted from optical motion capture systems, we tested our method on different subjects, and the quality of the recovered walking trajectory is evaluated.

NEW ADAPTIVE BARZILAI–BORWEIN STEP SIZE AND ITS APPLICATION IN SOLVING LARGE-SCALE OPTIMIZATION PROBLEMS

2018 ◽  
Vol 61 (1) ◽  
pp. 76-98 ◽  
Author(s):  
TING LI ◽  
ZHONG WAN
Keyword(s):  
Large Scale ◽  
Optimization Problems ◽  
Test Problems ◽  
Large Scale Optimization ◽  
Step Size ◽  
Quadratic Minimization ◽  
Minimization Problems ◽  
Ill Posed ◽  
Scale Optimization

We propose a new adaptive and composite Barzilai–Borwein (BB) step size by integrating the advantages of such existing step sizes. Particularly, the proposed step size is an optimal weighted mean of two classical BB step sizes and the weights are updated at each iteration in accordance with the quality of the classical BB step sizes. Combined with the steepest descent direction, the adaptive and composite BB step size is incorporated into the development of an algorithm such that it is efficient to solve large-scale optimization problems. We prove that the developed algorithm is globally convergent and it R-linearly converges when applied to solve strictly convex quadratic minimization problems. Compared with the state-of-the-art algorithms available in the literature, the proposed step size is more efficient in solving ill-posed or large-scale benchmark test problems.

scholarly journals On the Noise Complexity in an Optical Motion Capture Facility

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4435 ◽  
Author(s):  
Przemysław Skurowski ◽  
Magdalena Pawlyta
Keyword(s):  
Motion Capture ◽  
Noise Model ◽  
Regression Problem ◽  
Optical Motion ◽  
Optical Motion Capture ◽  
A Minor ◽  
Exploration Exploitation ◽  
Correlated Noises ◽  
Intrinsic Feature

Optical motion capture systems are state-of-the-art in motion acquisition; however, like any measurement system they are not error-free: noise is their intrinsic feature. The works so far mostly employ a simple noise model, expressing the uncertainty as a simple variance. In the work, we demonstrate that it might be not sufficient and we prove the existence of several types of noise and demonstrate how to quantify them using Allan variance. Such a knowledge is especially important for using optical motion capture to calibrate other techniques, and for applications requiring very fine quality of recording. For the automated readout of the noise coefficients, we solve the multidimensional regression problem using sophisticated metaheuristics in the exploration-exploitation scheme. We identified in the laboratory the notable contribution to the overall noise from white noise and random walk, and a minor contribution from blue noise and flicker, whereas the violet noise is absent. Besides classic types of noise we identified the presence of the correlated noises and periodic distortion. We analyzed also how the noise types scale with an increasing number of cameras. We had also the opportunity to observe the influence of camera failure on the overall performance.

scholarly journals Enhancing Elephant Herding Optimization with Novel Individual Updating Strategies for Large-Scale Optimization Problems

Mathematics ◽  
2019 ◽  
Vol 7 (5) ◽  
pp. 395 ◽  
Author(s):  
Jiang Li ◽  
Lihong Guo ◽  
Yan Li ◽  
Chang Liu
Keyword(s):  
Large Scale ◽  
Random Number ◽  
Optimization Problems ◽  
Large Scale Optimization ◽  
Weighted Sum ◽  
Test Functions ◽  
Scale Optimization ◽  
Previous Iteration ◽  
Improved Methods

Inspired by the behavior of elephants in nature, elephant herd optimization (EHO) was proposed recently for global optimization. Like most other metaheuristic algorithms, EHO does not use the previous individuals in the later updating process. If the useful information in the previous individuals were fully exploited and used in the later optimization process, the quality of solutions may be improved significantly. In this paper, we propose several new updating strategies for EHO, in which one, two, or three individuals are selected from the previous iterations, and their useful information is incorporated into the updating process. Accordingly, the final individual at this iteration is generated according to the elephant generated by the basic EHO, and the selected previous elephants through a weighted sum. The weights are determined by a random number and the fitness of the elephant individuals at the previous iteration. We incorporated each of the six individual updating strategies individually into the basic EHO, creating six improved variants of EHO. We benchmarked these proposed methods using sixteen test functions. Our experimental results demonstrated that the proposed improved methods significantly outperformed the basic EHO.

PENGUATAN KAPASITAS WIRAUSAHAWAN MIKRO MENGGUNAKAN METODE PENDAMPINGAN DI DESA MEKARGALIH, KECAMATAN JATINANGOR, KABUPATEN SUMEDANG

Dharmakarya ◽  
2020 ◽  
Vol 9 (2) ◽  
Author(s):  
RUDI Saprudin DARWIS
Keyword(s):  
Service Learning ◽  
Business Development ◽  
Small Scale ◽  
Learning Program ◽  
Student Service

ABSTRACTWeaknesses that are still commonly found in the businesses carried out by MSME entrepreneurs are the weakness of business accounting and packaging. Small scale business with limited marketing is seen as not requiring bookkeeping in its management and does not require packaging that is too good. This is the basis for the need for assistance to improve the capacity of MSME actors. Improving the capacity of MSME actors individually is done using the mentoring method. The choice to use a mentoring method to increase business productivity. Assistance was carried out with students of SMEs during the student service-learning program in Mekargalih Village, Jatinangor District, Sumedang Regency. Bookkeeping assistance is carried out by students by carrying out bookkeeping practices together so that the community can continue to learn good bookkeeping methods. Likewise, assistance in improving the quality of shredded chili packaging. Students help SMEs in designing packaging that will be used on their products. The assistance process is considered effective in supporting the business development of MSME entrepreneurs because the process can be carried out intensively. ABSTRAKKelemahan yang masih banyak ditemui pada usaha-usaha yang dilakukan pelaku UMKM adalah lemahnya pembukuan usaha dan pengemasannya. Skala usaha yang kecil dengan pemasaran yang terbatas dipandang tidak memerlukan pembukuan dalam pengelolaanya serta tidak memerlukan pengemasan yang terlalu bagus. Hal ini menjadi dasar perlunya dilakukan pendampingan untuk meningkatkan kapasitas pelaku UMKM. Peningkatan kapasitas pelaku UMKM secara perorangan dilakukan dengan menggunakan metode pendampingan. Pilihan untuk menggunakan metode pendampingan dalam meningkatkan produktivitas usahanya. Pendampingan dilakukan bersama mahasiswa terhadap pelaku UMKM selama pelaksanaan KKN mahasiswa di Desa Mekargalih, Kecamatan Jatinangor, Kabupaten Sumedang. Pendampingan pembukuan dilakukan mahasiswa dengan cara melakukan praktik pembukuan bersama-sama sehingga masyarakat bisa terus mempelajari cara pembukuan yang baik. Demikian juga dengan pendampingan dalam peningkatan mutu kualitas kemasan abon cabe. Mahasiswa membantu pelaku UMKM dalam merancang kemasan yang akan digunakan pada produknya. Proses pendampingan dinilai efektif dalam mendukung pengembangan usaha pelaku UMKM karena proses bisa dilakukan secara intensif.

Software suite for determining the tilts of tower-type structures according to terrestrial laser scanning

2020 ◽  
Vol 961 (7) ◽  
pp. 2-7
Author(s):  
A.V. Zubov ◽  
N.N. Eliseeva
Keyword(s):  
Laser Scanning ◽  
Optimization Problems ◽  
Optimization Methods ◽  
User Participation ◽  
Software Suite ◽  
Current State ◽  
Visual Basic For Applications ◽  
Operational Data ◽  
Theoretical Developments

The authors describe a software suite for determining tilt degrees of tower-type structures according to ground laser scanning indication. Defining the tilt of the pipe is carried out with a set of measured data through approximating the sections by circumferences. They are constructed using one of the simplest search engine optimization methods (evolutionary algorithm). Automatic filtering the scan of the current section from distorting data is performed by the method of assessing the quality of models constructed with that of least squares. The software was designed using Visual Basic for Applications. It contains several blocks (subprograms), with each of them performing a specific task. The developed complex enables obtaining operational data on the current state of the object with minimal user participation in the calculation process. The software suite is the result of practical implementing theoretical developments on the possibilities of using search methods at solving optimization problems in geodetic practice.

scholarly journals Multi-Task Optimization and Multi-Task Evolutionary Computation in the Past Five Years: A Brief Review

Mathematics ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 864
Author(s):  
Qingzheng Xu ◽  
Na Wang ◽  
Lei Wang ◽  
Wei Li ◽  
Qian Sun
Keyword(s):  
Evolutionary Computation ◽  
Explicit Knowledge ◽  
Optimization Problems ◽  
Effective Means ◽  
Typical Application ◽  
The Past ◽  
Current State ◽  
Evolution Algorithms ◽  
Application Fields

Traditional evolution algorithms tend to start the search from scratch. However, real-world problems seldom exist in isolation and humans effectively manage and execute multiple tasks at the same time. Inspired by this concept, the paradigm of multi-task evolutionary computation (MTEC) has recently emerged as an effective means of facilitating implicit or explicit knowledge transfer across optimization tasks, thereby potentially accelerating convergence and improving the quality of solutions for multi-task optimization problems. An increasing number of works have thus been proposed since 2016. The authors collect the abundant specialized literature related to this novel optimization paradigm that was published in the past five years. The quantity of papers, the nationality of authors, and the important professional publications are analyzed by a statistical method. As a survey on state-of-the-art of research on this topic, this review article covers basic concepts, theoretical foundation, basic implementation approaches of MTEC, related extension issues of MTEC, and typical application fields in science and engineering. In particular, several approaches of chromosome encoding and decoding, intro-population reproduction, inter-population reproduction, and evaluation and selection are reviewed when developing an effective MTEC algorithm. A number of open challenges to date, along with promising directions that can be undertaken to help move it forward in the future, are also discussed according to the current state. The principal purpose is to provide a comprehensive review and examination of MTEC for researchers in this community, as well as promote more practitioners working in the related fields to be involved in this fascinating territory.

scholarly journals ACO with Intuitionistic Fuzzy Pheromone Updating Applied on Multiple-Constraint Knapsack Problem

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1456
Author(s):  
Stefka Fidanova ◽  
Krassimir Todorov Atanassov
Keyword(s):  
Decision Making ◽  
Knapsack Problem ◽  
Propositional Logic ◽  
Optimization Problems ◽  
Real Life ◽  
Combinatorial Optimization Problems ◽  
Intuitionistic Fuzzy ◽  
Life Problems ◽  
Multiple Constraint

Some of industrial and real life problems are difficult to be solved by traditional methods, because they need exponential number of calculations. As an example, we can mention decision-making problems. They can be defined as optimization problems. Ant Colony Optimization (ACO) is between the best methods, that solves combinatorial optimization problems. The method mimics behavior of the ants in the nature, when they look for a food. One of the algorithm parameters is called pheromone, and it is updated every iteration according quality of the achieved solutions. The intuitionistic fuzzy (propositional) logic was introduced as an extension of Zadeh’s fuzzy logic. In it, each proposition is estimated by two values: degree of validity and degree of non-validity. In this paper, we propose two variants of intuitionistic fuzzy pheromone updating. We apply our ideas on Multiple-Constraint Knapsack Problem (MKP) and compare achieved results with traditional ACO.

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