Generation and Evaluation of a Manipulator Workspace Based on Optimum Path Search

1985 ◽  
Vol 107 (2) ◽  
pp. 245-255 ◽  
Author(s):  
M. Cwiakala ◽  
T. W. Lee
Keyword(s):  
Comparative Study ◽  
Quantitative Evaluation ◽  
Matrix Method ◽  
Optimization Technique ◽  
Industrial Robots ◽  
Dual Number ◽  
Revolute Joints ◽  
Computational Advantage ◽  
Optimum Path ◽  
Path Search

This paper presents an algorithm using an optimization technique to outline the boundary profile of a manipulator workspace and perform quantitative evaluation of the workspace volume. The algorithm is applicable to general N-link manipulators with not only the revolute joints, but also joints of other types, such as, the prismatic and cylindrical joints. It is a partial-scanning technique which offers significant reduction on the number of scanning points to generate the workspace and the method is particularly efficient in dealing with complicated manipulator geometry. The [3 × 3] dual-number matrix method is used as the basis for analytical formulations, and consequently, computational advantage is gained. A comparative study is given with a previously used algorithm. Several specific examples involving industrial robots of various kinds are given to demonstrate the capability of the algorithm.

scholarly journals Multi-criteria Optimization Technique with Complex Pythagorean Fuzzy N-soft Information

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Muhammad Akram ◽  
Faiza Wasim ◽  
José Carlos R. Alcantud ◽  
Ahmad N. Al-Kenani
Keyword(s):  
Decision Making ◽  
Comparative Study ◽  
Manufacturing Industry ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Fuzzy Topsis ◽  
Industrial Robots ◽  
Weighted Averaging ◽  
Topsis Method ◽  
Vikor Method

AbstractThe main objective of this article is to lay the foundations of a novel multi-criteria optimization technique, namely, the complex Pythagorean fuzzy N-soft VIKOR (CPFNS-VIKOR) method that is highly proficient to express a great deal of linguistic imprecision and vagueness inherent in human assessments. This strategy provides a versatile decision-making tool for the ranking-based fuzzy modeling of two-dimensional parameterized data. The CPFNS-VIKOR method integrates the ground-breaking specialities of the VIKOR method with the outstanding parametric structure of the complex Pythagorean fuzzy N-soft model. It is exclusively designed for the specification of a compromise optimal solution having maximum group utility and minimum individual regret of the opponent by analyzing their weighted proximity from ideal solutions. The developed strategy factually permits specific linguistic terms to demystify the individual perspectives of the decision-making experts regarding the efficacy of the alternatives and the priorities of the applicable criteria. We comprehensively assemble these independent appraisals of all the experts using the complex Pythagorean fuzzy N-soft weighted averaging operator. Moreover, we calibrate the ranking measure by utilizing group utility measure and regret measure in order to specify the hierarchical outranking of the feasible alternatives. We demonstrate the systematic methodology and framework of the proposed method with the assistance of an explicative flow chart. We skilfully investigate an empirical analysis related to selection of constructive industrial robots for the modernization of a manufacturing industry which really justifies the remarkable accountability of the proposed strategy. Furthermore, we validate this technique by a comparative study with the existing complex Pythagorean fuzzy TOPSIS (CPF-TOPSIS) method, complex Pythagorean fuzzy VIKOR (CPF-VIKOR) method and Pythagorean fuzzy TOPSIS (PF-TOPSIS) method. The comparative study is exemplified with an illustrative bar chart that visually endorses the rationality of the proposed methodology by interpreting highly compatible and accurate final outcomes. Finally, we holistically analyze the functionality of the developed strategy to enlighten its merits and prominence over other available competent approaches.

Comparative study between the results of effective index based matrix method and characterization of fabricated SU-8 waveguide

2017 ◽  
Vol 382 ◽  
pp. 632-638 ◽  
Author(s):  
Swagata Samanta ◽  
Pradip Kumar Dey ◽  
Pallab Banerji ◽  
Pranabendu Ganguly
Keyword(s):  
Comparative Study ◽  
Matrix Method ◽  
Effective Index

Determining the Energy-Optimal Base Position of Industrial Robots by Means of the Modelica Multi-Physics Language

2014 ◽  
Vol 680 ◽  
pp. 320-325 ◽  
Author(s):  
Michele Gadaleta ◽  
Andrea Genovesi ◽  
Federico Balugani
Keyword(s):  
Energy Demand ◽  
Industrial Robot ◽  
Optimization Technique ◽  
Minimum Energy ◽  
Industrial Robots ◽  
Task Completion ◽  
Simulation Environment ◽  
Minimum Energy Consumption ◽  
Base Position ◽  
Time Required

A novel technique for determining the energy-optimal base position of common Industrial Robot (IR) is presented. At first, an energy-focused IR model is developed by means of the Modelica/Dymola simulation environment. Then, for a given IR task, a standard but efficient optimization technique is employed, which allows to determine the robot base position corresponding to the minimum energy consumption. A set of graphical maps is finally provided, which allows a rapid estimation of the energy demand along with the time required for the task completion.

A Comparative Study on the Pick-and-Place Trajectories for a Delta Robot

2016 ◽  
Author(s):  
Zexiao Xie ◽  
Peixin Wu ◽  
Ping Ren
Keyword(s):  
Comparative Study ◽  
High Speed ◽  
Computation Time ◽  
Optimization Methods ◽  
Terminal State ◽  
Industrial Robots ◽  
Piecewise Polynomials ◽  
Pick And Place ◽  
Dynamic Performances ◽  
Delta Robot

A comparative study on the pick-and-place trajectories for high-speed Delta robots is presented in this paper. The Adept Cycle has been widely accepted as a standardized pick-and-place trajectory for industrial robots. The blending curves and optimization methods to smooth this trajectory are briefly surveyed. Three major types of trajectories: Lamé curves, clothoids and piecewise polynomials, are selected as candidates to be compared. The processes to generate these trajectories are briefly reviewed. The trajectories are firstly compared in term of their computation time. Then, based on a dynamic model and an experimental prototype of the Delta robot, different combinations of the geometric paths and motion profiles are compared in terms of power consumption, terminal state accuracy and residual vibration. The effects of trajectory configurations and parameters on the robot’s dynamic performances are investigated. Through a comprehensive analysis on both simulation and experimental results, a near-optimal pick-and-place trajectory for the Delta robot is identified and validated.

Structural dynamics of the foldable stairs

2012 ◽  
Vol 226 (10) ◽  
pp. 2549-2572 ◽  
Author(s):  
Jing-Shan Zhao ◽  
Jian-Yi Wang ◽  
Fu-Lei Chu ◽  
Zhi-Jing Feng ◽  
Jian S Dai
Keyword(s):  
Boundary Conditions ◽  
Transfer Matrix ◽  
Structural Dynamics ◽  
Transfer Matrix Method ◽  
Matrix Method ◽  
Huge Number ◽  
Traditional Methods ◽  
Revolute Joints ◽  
Dynamics Method

This article proposes a structural dynamics method for foldable stairs based on transfer matrix. The stairs are made up of a number of identical scissor-like elements which are supposed to be Euler–Bernoulli beams. The dynamics of each segment beam between every two adjacent revolute joints can be precisely expressed by the transfer matrix of the segment with the variables of boundary conditions of the joints. Therefore, the structural dynamics of the whole stairs is built using the least number of variables compared with the traditional methods. In addition, this method avoids the problem of the traditional transfer-matrix method that the number of variables greatly increases when there are a huge number of cross-joints within a structure.

Optimal path search and control of mobile robot using hybridized sine-cosine algorithm and ant colony optimization technique

2020 ◽  
Vol 47 (4) ◽  
pp. 535-545
Author(s):  
Saroj Kumar ◽  
Dayal R. Parhi ◽  
Manoj Kumar Muni ◽  
Krishna Kant Pandey
Keyword(s):  
Mobile Robots ◽  
Ant Colony Optimization ◽  
Optimization Technique ◽  
Optimal Path ◽  
Ant Colony ◽  
Target Point ◽  
Multiple Mobile Robots ◽  
Content Type ◽  
Path Search ◽  
Sine Cosine Algorithm

Purpose This paper aims to incorporate a hybridized advanced sine-cosine algorithm (ASCA) and advanced ant colony optimization (AACO) technique for optimal path search with control over multiple mobile robots in static and dynamic unknown environments. Design/methodology/approach The controller for ASCA and AACO is designed and implemented through MATLAB simulation coupled with real-time experiments in various environments. Whenever the sensors detect obstacles, ASCA is applied to find their global best positions within the sensing range, following which AACO is activated to choose the next stand-point. This is how the robot travels to the specified target point. Findings Navigational analysis is carried out by implementing the technique developed here using single and multiple mobile robots. Its efficiency is authenticated through the comparison between simulation and experimental results. Further, the proposed technique is found to be more efficient when compared with existing methodologies. Significant improvements of about 10.21 per cent in path length are achieved along with better control over these. Originality/value Systematic presentation of the proposed technique attracts a wide readership among researchers where AI technique is the application criteria.

scholarly journals Applications of Artificial Intelligence Techniques to Enhance Sustainability of Industry 4.0: Design of an Artificial Neural Network Model as Dynamic Behavior Optimizer of Robotic Arms

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-10 ◽  
Author(s):  
Aydin Azizi
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Artificial Neural Network ◽  
Industrial Robots ◽  
Optimal Parameters ◽  
Ann Model ◽  
Robotic Arms ◽  
Revolute Joints ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

Industrial robots have a great impact on increasing the productivity and reducing the time of the manufacturing process. To serve this purpose, in the past decade, many researchers have concentrated to optimize robotic models utilizing artificial intelligence (AI) techniques. Gimbal joints because of their adjustable mechanical advantages have been investigated as a replacement for traditional revolute joints, especially when they are supposed to have tiny motions. In this research, the genetic algorithm (GA), a well-known evolutionary technique, has been adopted to find optimal parameters of the gimbal joints. Since adopting the GA is a time-consuming process, an artificial neural network (ANN) architecture has been proposed to model the behavior of the GA. The result shows that the proposed ANN model can be used instead of the complex and time-consuming GA in the process of finding the optimal parameters of the gimbal joint.

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