scholarly journals Improving the Manipulability of a Redundant Arm Using Decoupled Hybrid Visual Servoing

2021 ◽  
Vol 11 (23) ◽  
pp. 11566
Author(s):  
Alireza Rastegarpanah ◽  
Ali Aflakian ◽  
Rustam Stolkin
Keyword(s):  
Real World ◽  
Projection Operator ◽  
Secondary Task ◽  
Visual Servoing ◽  
Least Square ◽  
Visual Features ◽  
Speed Up ◽  
3D Estimation

This study proposes a hybrid visual servoing technique that is optimised to tackle the shortcomings of classical 2D, 3D and hybrid visual servoing approaches. These shortcomings are mostly the convergence issues, image and robot singularities, and unreachable trajectories for the robot. To address these deficiencies, 3D estimation of the visual features was used to control the translations in Z-axis as well as all rotations. To speed up the visual servoing (VS) operation, adaptive gains were used. Damped Least Square (DLS) approach was used to reduce the robot singularities and smooth out the discontinuities. Finally, manipulability was established as a secondary task, and the redundancy of the robot was resolved using the classical projection operator. The proposed approach is compared with the classical 2D, 3D and hybrid visual servoing methods in both simulation and real-world. The approach offers more efficient trajectories for the robot, with shorter camera paths than 2D image-based and classical hybrid VS methods. In comparison with the traditional position-based approach, the proposed method is less likely to lose the object from the camera scene, and it is more robust to the camera calibrations. Moreover, the proposed approach offers greater robot controllability (higher manipulability) than other approaches.

scholarly journals A Lower Bound for the Query Phase of Contraction Hierarchies and Hub Labels and a Provably Optimal Instance-Based Schema

Algorithms ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 164
Author(s):  
Tobias Rupp ◽  
Stefan Funke
Keyword(s):  
Lower Bound ◽  
Lower Bounds ◽  
Real World ◽  
Road Network ◽  
Upper And Lower Bounds ◽  
Bounded Degree ◽  
Shortest Path Routing ◽  
Graph Classes ◽  
Speed Up ◽  
To Come

We prove a Ω(n) lower bound on the query time for contraction hierarchies (CH) as well as hub labels, two popular speed-up techniques for shortest path routing. Our construction is based on a graph family not too far from subgraphs that occur in real-world road networks, in particular, it is planar and has a bounded degree. Additionally, we borrow ideas from our lower bound proof to come up with instance-based lower bounds for concrete road network instances of moderate size, reaching up to 96% of an upper bound given by a constructed CH. For a variant of our instance-based schema applied to some special graph classes, we can even show matching upper and lower bounds.

scholarly journals A CDT-Based Heuristic Zone Design Approach for Economic Census Investigators

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Changixu Cheng ◽  
Xiaomei Song ◽  
Jing Yang ◽  
Xiatian Hu ◽  
Shi Shen ◽  
...  
Keyword(s):  
Delaunay Triangulation ◽  
Real World ◽  
Heuristic Method ◽  
Real World Application ◽  
Economic Census ◽  
Speed Up ◽  
Growth Approach ◽  
Special Zone ◽  
Required Quality

This paper addresses a special zone design problem for economic census investigators that is motivated by a real-world application. This paper presented a heuristic multikernel growth approach via Constrained Delaunay Triangulation (CDT). This approach not only solved the barriers problem but also dealt with the polygon data in zoning procedure. In addition, it uses a new heuristic method to speed up the zoning process greatly on the premise of the required quality of zoning. At last, two special instances for economic census were performed, highlighting the performance of this approach.

Opposition-based learning Multi-Verse Optimizer with disruption operator for optimization problems

2021 ◽  
Author(s):  
Mohammad Shehab ◽  
Laith Abualigah
Keyword(s):  
Real World ◽  
Optimization Problems ◽  
Second Stage ◽  
Opposition Based Learning ◽  
High Fitness ◽  
Fitness Value ◽  
Speed Up ◽  
Disruption Operator ◽  
The Given ◽  
Real World Problems

Abstract Multi-Verse Optimizer (MVO) algorithm is one of the recent metaheuristic algorithms used to solve various problems in different fields. However, MVO suffers from a lack of diversity which may trapping of local minima, and premature convergence. This paper introduces two steps of improving the basic MVO algorithm. The first step using Opposition-based learning (OBL) in MVO, called OMVO. The OBL aids to speed up the searching and improving the learning technique for selecting a better generation of candidate solutions of basic MVO. The second stage, called OMVOD, combines the disturbance operator (DO) and OMVO to improve the consistency of the chosen solution by providing a chance to solve the given problem with a high fitness value and increase diversity. To test the performance of the proposed models, fifteen CEC 2015 benchmark functions problems, thirty CEC 2017 benchmark functions problems, and seven CEC 2011 real-world problems were used in both phases of the enhancement. The second step, known as OMVOD, incorporates the disruption operator (DO) and OMVO to improve the accuracy of the chosen solution by giving a chance to solve the given problem with a high fitness value while also increasing variety. Fifteen CEC 2015 benchmark functions problems, thirty CEC 2017 benchmark functions problems and seven CEC 2011 real-world problems were used in both phases of the upgrade to assess the accuracy of the proposed models.

An Efficient Pruning and Filtering Strategy to Mine Partial Periodic Patterns from a Sequence of Event Sets

2014 ◽  
Vol 10 (2) ◽  
pp. 18-38 ◽  
Author(s):  
Kung-Jiuan Yang ◽  
Tzung-Pei Hong ◽  
Yuh-Min Chen ◽  
Guo-Cheng Lan
Keyword(s):  
Time Series ◽  
Real World ◽  
Oil Price ◽  
Time Stamp ◽  
Single Event ◽  
Periodic Patterns ◽  
Event Time ◽  
The Past ◽  
Real World Applications ◽  
Speed Up

Partial periodic patterns are commonly seen in real-world applications. The major problem of mining partial periodic patterns is the efficiency problem due to a huge set of partial periodic candidates. Although some efficient algorithms have been developed to tackle the problem, the performance of the algorithms significantly drops when the mining parameters are set low. In the past, the authors have adopted the projection-based approach to discover the partial periodic patterns from single-event time series. In this paper, the authors extend it to mine partial periodic patterns from a sequence of event sets which multiple events concurrently occur at the same time stamp. Besides, an efficient pruning and filtering strategy is also proposed to speed up the mining process. Finally, the experimental results on a synthetic dataset and real oil price dataset show the good performance of the proposed approach.

scholarly journals Model-free vision-based shaping of deformable plastic materials

2020 ◽  
Vol 39 (14) ◽  
pp. 1739-1759 ◽  
Author(s):  
Andrea Cherubini ◽  
Valerio Ortenzi ◽  
Akansel Cosgun ◽  
Robert Lee ◽  
Peter Corke
Keyword(s):  
Neural Network ◽  
Pilot Study ◽  
Visual Servoing ◽  
Robotic Arm ◽  
Visual Features ◽  
Heuristic Methods ◽  
Outer Contour ◽  
Model Free ◽  
Contour Shape ◽  
Plastic Materials

We address the problem of shaping deformable plastic materials using non-prehensile actions. Shaping plastic objects is challenging, because they are difficult to model and to track visually. We study this problem, by using kinetic sand, a plastic toy material that mimics the physical properties of wet sand. Inspired by a pilot study where humans shape kinetic sand, we define two types of actions: pushing the material from the sides and tapping from above. The chosen actions are executed with a robotic arm using image-based visual servoing. From the current and desired view of the material, we define states based on visual features such as the outer contour shape and the pixel luminosity values. These are mapped to actions, which are repeated iteratively to reduce the image error until convergence is reached. For pushing, we propose three methods for mapping the visual state to an action. These include heuristic methods and a neural network, trained from human actions. We show that it is possible to obtain simple shapes with the kinetic sand, without explicitly modeling the material. Our approach is limited in the types of shapes it can achieve. A richer set of action types and multi-step reasoning is needed to achieve more sophisticated shapes.

Cashless Payments and its Impact on Inflation

2020 ◽  
Vol 7 (9) ◽  
pp. 524-532
Author(s):  
Pisi Bethania Titalessy
Keyword(s):  
Credit Card ◽  
Least Square ◽  
Research Approach ◽  
Electronic Money ◽  
Ordinary Least Square ◽  
Cash Transaction ◽  
Speed Up ◽  
Using Data ◽  
Relationship Of ◽  
The Relationship

Payment with a non-cash system can simplify transactions and are increasingly used. The advantages of non-cash payments are not only due to convenience, speed up transaction time, and time savings but also the benefits that can reduce the circulation of money in the community. The less the amount of physical money in circulation, it will indirectly affect the inflation rate. However, there are inconsistency of research results regarding the relationship of non-cash transactions and inflation. These issues constitute a research gap on cashless payments and inflation in Indonesia. This study aims to prove the relationship between cashless payments and inflation in Indonesia. Using data from Central Bureau of Statistics Republic of Indonesia and Bank Indonesia over the period 2019-2020Q2, the results confirm that electronic money decrease inflation. The research approach in this study focuses on quantitative analysis using the Ordinary Least Square (OLS) method. The results of this study indicate that partially the relationship between debit card transactions and inflation has no significant effect. Credit card transactions have no significant effect on inflation, while electronic money transactions have a significant effect on inflation in Indonesia. Non-cash transactions intensified by Bank Indonesia through the cash-less society need to be considered more with the public's understanding of the use of non-cash transaction instruments so that the use of non-cash transactions in Indonesia is not only used for cash withdrawals but is used in every transaction.

VISION BASED MOTION CONTROL AND TRAJECTORY TRACKING FOR MICROASSEMBLY ROBOTS

2007 ◽  
Vol 04 (03) ◽  
pp. 237-249
Author(s):  
MIN WANG ◽  
XIADONG LV ◽  
XINHAN HUANG
Keyword(s):  
Motion Control ◽  
Trajectory Tracking ◽  
Visual Servoing ◽  
Control Method ◽  
Focal Depth ◽  
Least Square ◽  
Energy Curve ◽  
Least Square Estimator ◽  
Robotic Motion ◽  
Optimizing Control

This paper presents a vision based motion control and trajectory tracking strategies for microassembly robots including a self-optimizing visual servoing depth motion control method and a novel trajectory snake tracking strategy. To measure micromanipulator depth motion, a normalized gray-variance focus measure operator is developed using depth from focus techniques. The extracted defocus features are theoretically distributed with one peak point which can be applied to locate the microscopic focal depth via self-optimizing control. Tracking differentiators are developed to suppress noises and track the features and their differential values without oscillation. Based on the differential defocus signals a coarse-to-fine self-optimizing controller is presented for micromanipulator to precisely locate focus depth. As well as a novel trajectory snake energy function of robotic motion is defined involving kinematic energy, curve potential and image potential energy. The motion trajectory can be located through searching the converged energy distribution of the snake function. Energy weights in the function are real-time adjusted to avoid local minima during convergence. To improve snake searching efficiency, quadratic-trajectory least square estimator is employed to predict manipulator motion position before tracking. Experimental results in a microassembly robotic system demonstrate that the proposed strategies are successful and effective.

The Constrained Least-Square Optimization of Spherical Four-Bar Path Generators

1992 ◽  
Vol 114 (3) ◽  
pp. 394-405 ◽  
Author(s):  
J. Angeles ◽  
Z. Liu
Keyword(s):  
Numerical Procedure ◽  
Orthogonal Decomposition ◽  
Least Square ◽  
System Of Nonlinear Equations ◽  
Overdetermined System ◽  
Optimization Scheme ◽  
Numerical Examples ◽  
Speed Up ◽  
General Basis ◽  
Four Bar Linkage

In this paper, the optimization of the spherical RRRR four-bar linkage for the problem of path generation is addressed. The problem is formulated as a two-loop minimization of the error between the path-generating point in the coupler curve and the prescribed position, while decoupling the linkage parameters from the configuration variables, namely, the input angles. The synthesis problem consists of evaluating a set of input angles {ψk}1m defining m linkage configurations and the linkage parameters independently. This leads to a constrained overdetermined system of nonlinear equations. The orthogonal decomposition algorithm, introduced elsewhere, is employed to solve the problem. Continuation and damping techniques are used in the numerical procedure to ensure convergence and speed up its rate. The optimization scheme is developed on a general basis and can handle the problem for any number of given path points. Three numerical examples are included.

Crash and Near-Crash Risk Assessment of Distracted Driving and Engagement in Secondary Tasks: A Naturalistic Driving Study

2018 ◽  
Vol 2672 (38) ◽  
pp. 245-254 ◽  
Author(s):  
Peter R. Bakhit ◽  
BeiBei Guo ◽  
Sherif Ishak
Keyword(s):  
Traffic Safety ◽  
Real World ◽  
Secondary Task ◽  
Safety Concern ◽  
Distracted Driving ◽  
Crash Risk ◽  
Secondary Tasks ◽  
Depth Analysis ◽  
Naturalistic Driving Study ◽  
Naturalistic Driving

Distracted driving behavior is a perennial safety concern that affects not only the vehicle’s occupants but other road users as well. Distraction is typically caused by engagement in secondary tasks and activities such as manipulating objects and passenger interaction, among many others. This study provides an in-depth analysis of the increased crash/near-crash risk associated with different secondary tasks using the largest real-world naturalistic driving dataset (SHRP2 Naturalistic Driving Study). Several statistical and data-mining techniques were developed to analyze the distracted driving and crash risk. First, a bivariate probit model was constructed to investigate the relationship between engagement in a secondary task and the safety-critical events likelihood. Subsequently, two different techniques were implemented to quantify the increased crash/near-crash risk because of involvement in a particular secondary task. The first technique used the baseline-category logits model to estimate the increased crash risk in terms of conditional odds ratios. The second technique used the a priori association rule mining algorithm to reveal the risk associated with each secondary task in terms of support, confidence, and lift indexes. The results indicate that reaching for objects, manipulating objects, reading, and cell phone texting are the highest crash risk factors among various secondary tasks. Recognizing the effect of different secondary tasks on traffic safety in a real-world environment helps legislators enact laws that reduce crashes resulting from distracted driving, as well as enabling government officials to make informed decisions about the allocation of available resources to reduce roadway crashes and improve traffic safety.

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