Investigating the potential of redundant manipulators in narrow channels

2020 ◽  
pp. 095440622096451
Author(s):  
Ashish Singla ◽  
Jyotindra Narayan ◽  
Himanshu Arora
Keyword(s):  
Case Studies ◽  
Fuzzy Inference ◽  
Redundant Manipulators ◽  
Redundancy Resolution ◽  
Inference System ◽  
Narrow Channels ◽  
First Case ◽  
Task Priority ◽  
Patient Side

In this paper, an attempt has been made to investigate the potential of redundant manipulators, while tracking trajectories in narrow channels. The behavior of redundant manipulators is important in many challenging applications like under-water welding in narrow tanks, checking the blockage in sewerage pipes, performing a laparoscopy operation etc. To demonstrate this snake-like behavior, redundancy resolution scheme is utilized using two different approaches. The first approach is based on the concept of task priority, where a given task is split and prioritize into several subtasks like singularity avoidance, obstacle avoidance, torque minimization, and position preference over orientation etc. The second approach is based on Adaptive Neuro Fuzzy Inference System (ANFIS), where the training is provided through given datasets and the results are back-propagated using augmentation of neural networks with fuzzy logics. Three case studies are considered in this work to demonstrate the redundancy resolution of serial manipulators. The first case study of 3-link manipulator is attempted with both the approaches, where the objective is to track the desired trajectory while avoiding multiple obstacles. The second case study of 7-link manipulator, tracking trajectory in a narrow channel, is investigated using the concept of task priority. The realistic application of minimum-invasive surgery (MIS) based trajectory tracking is considered as the third case study, which is attempted using ANFIS approach. The 5-link spatial redundant manipulator, also known as a patient-side manipulator being developed at CSIR-CSIO, Chandigarh is used to track the desired surgical cuts. Through the three case studies, it is well demonstrated that both the approaches are giving satisfactory results.

Sustainable management of water demand using fuzzy inference system: a case study of Kenyir Lake, Malaysia

2021 ◽  
Author(s):  
Nor Najwa Irina Mohd Azlan ◽  
Marlinda Abdul Malek ◽  
Maslina Zolkepli ◽  
Jamilah Mohd Salim ◽  
Ali Najah Ahmed
Keyword(s):  
Fuzzy Inference System ◽  
Water Demand ◽  
Sustainable Management ◽  
Fuzzy Inference ◽  
Inference System ◽  
System A

A new meta-heuristic optimization algorithm based on a paradigm from physics: string theory

2021 ◽  
Vol 41 (1) ◽  
pp. 1657-1675
Author(s):  
Luis Rodriguez ◽  
Oscar Castillo ◽  
Mario Garcia ◽  
Jose Soria
Keyword(s):  
String Theory ◽  
Optimization Algorithm ◽  
Fuzzy Inference ◽  
Fuzzy Controller ◽  
Optimization Problems ◽  
Flower Pollination Algorithm ◽  
Grey Wolf Optimizer ◽  
Mathematical Functions ◽  
Inference System ◽  
First Case

The main goal of this paper is to outline a new optimization algorithm based on String Theory, which is a relative new area of physics. The String Theory Algorithm (STA) is a nature-inspired meta-heuristic, which is based on studies about a theory stating that all the elemental particles that exist in the universe are strings, and the vibrations of these strings create all particles existing today. The newly proposed algorithm uses equations based on the laws of physics that are stated in String Theory. The main contribution in this proposed method is the new techniques that are devised in order to generate potential solutions in optimization problems, and we are presenting a detailed explanation and the equations involved in the new algorithm in order to solve optimization problems. In this case, we evaluate this new proposed meta-heuristic with three cases. The first case is of 13 traditional benchmark mathematical functions and a comparison with three different meta-heuristics is presented. The three algorithms are: Flower Pollination Algorithm (FPA), Firefly Algorithm (FA) and Grey Wolf Optimizer (GWO). The second case is the optimization of benchmark functions of the CEC 2015 Competition and we are also presenting a statistical comparison of these results with respect to FA and GWO. In addition, we are presenting a third case, which is the optimization of a fuzzy inference system (FIS), specifically finding the optimal design of a fuzzy controller, where the main goal is to optimize the membership functions of the FIS. It is important to mention that we used these study cases in order to analyze the proposed meta-heuristic with: basic problems, complex problems and control problems. Finally, we present the performance, results and conclusions of the new proposed meta-heuristic.

scholarly journals Systemic Design: Two Canadian Case Studies

2014 ◽  
Vol 7 (3) ◽  
Author(s):  
Alex Ryan ◽  
Mark Leung
Keyword(s):  
Resource Management ◽  
Case Studies ◽  
Systems Thinking ◽  
Management System ◽  
Design Thinking ◽  
Clean Energy ◽  
Resource Management System ◽  
First Case ◽  
Systemic Design

This paper introduces two novel applications of systemic design to facilitate a comparison of alternative methodologies that integrate systems thinking and design. In the first case study, systemic design helped the Procurement Department at the University of Toronto re-envision how public policy is implemented and how value is created in the broader university purchasing ecosystem. This resulted in an estimated $1.5 million in savings in the first year, and a rise in user retention rates from 40% to 99%. In the second case study, systemic design helped the clean energy and natural resources group within the Government of Alberta to design a more efficient and effective resource management system and shift the way that natural resource departments work together. This resulted in the formation of a standing systemic design team and contributed to the creation of an integrated resource management system. A comparative analysis of the two projects identifies a shared set of core principles for systemic design as well as areas of differentiation that reveal potential for learning across methodologies. Together, these case studies demonstrate the complementarity of systems thinking and design thinking, and show how they may be integrated to guide positive change within complex sociotechnical systems.

scholarly journals Using Model Performance to Assess the Representativeness of Data for Model Development and Calibration in Financial Institutions

Risks ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 204
Author(s):  
Chamay Kruger ◽  
Willem Daniel Schutte ◽  
Tanja Verster
Keyword(s):  
Case Studies ◽  
Model Development ◽  
Model Performance ◽  
Data Set ◽  
Pooled Data ◽  
External Data ◽  
First Case ◽  
Multivariate Prediction ◽  
Credit Data

This paper proposes a methodology that utilises model performance as a metric to assess the representativeness of external or pooled data when it is used by banks in regulatory model development and calibration. There is currently no formal methodology to assess representativeness. The paper provides a review of existing regulatory literature on the requirements of assessing representativeness and emphasises that both qualitative and quantitative aspects need to be considered. We present a novel methodology and apply it to two case studies. We compared our methodology with the Multivariate Prediction Accuracy Index. The first case study investigates whether a pooled data source from Global Credit Data (GCD) is representative when considering the enrichment of internal data with pooled data in the development of a regulatory loss given default (LGD) model. The second case study differs from the first by illustrating which other countries in the pooled data set could be representative when enriching internal data during the development of a LGD model. Using these case studies as examples, our proposed methodology provides users with a generalised framework to identify subsets of the external data that are representative of their Country’s or bank’s data, making the results general and universally applicable.

scholarly journals Use of Jacobians for inverse kinematics of articulated robots : a study on approximate solutions

2020 ◽  
Author(s):  
◽  
Uriel Jacket Tresor Demby's
Keyword(s):  
Numerical Solution ◽  
Inverse Kinematics ◽  
Degrees Of Freedom ◽  
Numerical Solutions ◽  
Fuzzy Inference ◽  
Numerical Approach ◽  
Data Driven ◽  
Approximate Methods ◽  
Inference System ◽  
First Case

In the context of articulated robotic manipulators, the Forward Kinematics (FK) is a highly non-linear function that maps joint configurations of the robot to poses of its endeffector. Furthermore, while in the most useful cases these functions are neither injective (one-to-one) nor surjective (onto), depending on the robot configuration -- i.e. the sequence of prismatic versus revolute joints, and the number of Degrees of Freedom (DoF) -- the associated Inverse Kinematics (IK) problem may be practically or even theoretically impossible to be solved analytically. Therefore, in the past decades, several approximate methods have been developed for many instances of IK problems. The approximate methods can be divided into two distinct categories: data-driven and numerical approaches. In the first case, data-driven approaches have been successfully used for small workspace domains (e.g., task-driven applications), but not fully explored for large ones, i.e. in task-independent applications where a more general IK is required. Similarly, and despite many successful implementations over the years, numerical solutions may fail if an improper matrix inverse is employed (e.g., Moore-Penrose generalized inverse). In this research, we propose a systematic, robust and accurate numerical solution for the IK problem using the Unit-Consistent (UC) and the Mixed (MX) Inverse methods to invert the Jacobians derived from the Denavit-Hartenberg (D-H) representation of the FK for any robot. As we demonstrate, this approach is robust to whether the system is underdetermined (less than 6 DoF) or overdetermined (more than 6 DoF). We compare the proposed numerical solution to data driven solutions using different robots -- with DoF varying from 3 to 7. We conclude that numerical solutions are easier to implement, faster, and more accurate than most data-driven approaches in the literature, specially for large workspaces as in task-independent applications. We particularly compared the proposed numerical approach against two data-driven approaches: Multi-Layer Perceptron (MLP) and Adaptive Neuro-Fuzzy Inference System (ANFIS), while exploring various architectures of these Neural Networks (NN): i.e. number of inputs, number of outputs, depth, and number of nodes in the hidden layers.

scholarly journals SABRE observations of Pi2 pulsations: case studies

1997 ◽  
Vol 15 (1) ◽  
pp. 40-53 ◽  
Author(s):  
E. G. Bradshaw ◽  
M. Lester
Keyword(s):  
Case Studies ◽  
Magnetic Activity ◽  
Auroral Zone ◽  
Field Of View ◽  
Ionospheric Currents ◽  
Pi2 Pulsation ◽  
First Case ◽  
Pi2 Pulsations ◽  
Generation Region

Abstract. The characteristics of substorm-associated Pi2 pulsations observed by the SABRE coherent radar system during three separate case studies are presented. The SABRE field of view is well positioned to observe the differences between the auroral zone pulsation signature and that observed at mid-latitudes. During the first case study the SABRE field of view is initially in the eastward electrojet, equatorward and to the west of the substorm-enhanced electrojet current. As the interval progresses, the western, upward field-aligned current of the substorm current wedge moves westward across the longitudes of the radar field of view. The westward motion of the wedge is apparent in the spatial and temporal signatures of the associated Pi2 pulsation spectra and polarisation sense. During the second case study, the complex field-aligned and ionospheric currents associated with the pulsation generation region move equatorward into the SABRE field of view and then poleward out of it again after the third pulsation in the series. The spectral content of the four pulsations during the interval indicate different auroral zone and mid-latitude signatures. The final case study is from a period of low magnetic activity when SABRE observes a Pi2 pulsation signature from regions equatorward of the enhanced substorm currents. There is an apparent mode change between the signature observed by SABRE in the ionosphere and that on the ground by magnetometers at latitudes slightly equatorward of the radar field of view. The observations are discussed in terms of published theories of the generation mechanisms for this type of pulsation. Different signatures are observed by SABRE depending on the level of magnetic activity and the position of the SABRE field of view relative to the pulsation generation region. A twin source model for Pi2 pulsation generation provides the clearest explanation of the signatures observed.

Mathematical Metaphors Gone Wild

2017 ◽  
Author(s):  
Roi Wagner
Keyword(s):  
Early Modern ◽  
Case Studies ◽  
Cognitive Theory ◽  
Early Modernity ◽  
First Case ◽  
Mathematical Life ◽  
George Lakoff

This chapter examines two case studies that illustrate the limitations of the cognitive theory of mathematical metaphor in accounting for the formation of actual historical mathematical life worlds. The first case study deals with four medieval and early modern examples of relating algebra to geometry. These examples show that when two mathematical domains are linked, what passes between them cannot be reduced to “inferences,” as assumed by the theory of mathematical metaphor. The second case study reviews notions of infinity since early modernity and demonstrates that these notions are far too variegated and complex to be subsumed under a single metaphor—namely, George Lakoff and Rafael Núñez's basic metaphor of infinity, which tries to read all mathematical infinities as metaphorically projecting final destinations on indefinite sequences.

Two Case Studies of Semiosis in Mathematics

2017 ◽  
Author(s):  
Roi Wagner
Keyword(s):  
Gender Role ◽  
Case Studies ◽  
Generating Functions ◽  
Stable Marriage ◽  
Mathematical Language ◽  
Stable Marriage Problem ◽  
Marriage Problem ◽  
First Case ◽  
Mathematical Signs

This chapter presents two case studies that highlight the problems of mathematical semiosis: how mathematical signs obtain and change their senses. The first case study follows the paradigmatic mathematical sign, x, as it is used in applications of powers series to combinatorics via generating functions. The second case study concerns gender role stereotypes involving the so-called “stable marriage problem.” Both case studies open up questions of how meaning is transferred within and across mathematical contexts and try to substantiate the book's claims about interpretation, formalization, and constraints over mathematical objects and statements. The chapter also considers gender-neutral mathematical language in the context of sexuality.

Interval type-2 fuzzy inference-based failure mode and effect analysis model in a group decision-making setting

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
İlker Gölcük
Keyword(s):  
Failure Modes ◽  
Fuzzy Inference ◽  
Real Life ◽  
Effect Analysis ◽  
Inference System ◽  
Content Type ◽  
Proposed Model ◽  
Interval Type

PurposeThis paper proposes an integrated IT2F-FMEA model under a group decision-making setting. In risk assessment models, experts' evaluations are often aggregated beforehand, and necessary computations are performed, which in turn, may cause a loss of information and valuable individual opinions. The proposed integrated IT2F-FMEA model aims to calculate risk priority numbers from the experts' evaluations and then fuse experts' judgments using a novel integrated model.Design/methodology/approachThis paper presents a novel failure mode and effect analysis (FMEA) model by integrating the fuzzy inference system, best-worst method (BWM) and weighted aggregated sum-product assessment (WASPAS) methods under interval type-2 fuzzy (IT2F) environment. The proposed FMEA approach utilizes the Mamdani-type IT2F inference system to calculate risk priority numbers. The individual FMEA results are combined by using integrated IT2F-BWM and IT2F-WASPAS methods.FindingsThe proposed model is implemented in a real-life case study in the furniture industry. According to the case study, fifteen failure modes are considered, and the proposed integrated method is used to prioritize the failure modes.Originality/valueMamdani-type singleton IT2F inference model is employed in the FMEA. Additionally, the proposed model allows experts to construct their membership functions and fuzzy rules to capitalize on the experience and knowledge of the experts. The proposed group FMEA model aggregates experts' judgments by using IT2F-BWM and IT2F-WASPAS methods. The proposed model is implemented in a real-life case study in the furniture company.

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