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Article
Publication date: 6 September 2011

Cui Hutao, Cheng Xiaojun, Xu Rui and Cui Pingyuan

The purpose of this paper is to propose an attitude control algorithm for spacecraft with geometric constraints.

Abstract

Purpose

The purpose of this paper is to propose an attitude control algorithm for spacecraft with geometric constraints.

Design/methodology/approach

The geometric constraint is reformulated as a quadratic form when quaternion is used as attitude parameter, then the constraint is proved to be nonconvex and is further transformed to a convex one. By designing a new constraint formulation to satisfy the real constraint in the predictive horizon, the attitude control problem is reshaped to a convex planning problem which is based on receding horizon control.

Findings

The proposed algorithm is more effective in handling geometric constraints than previous research which used single step planning control.

Practical implications

With novel improvements to current methods for steering spacecraft from one attitude to another with geometric constraints, great attitude maneuver path can be achieved to protect instruments and meanwhile satisfy mission requirements.

Originality/value

The attitude control algorithm in this paper is designed especially for the satisfaction of geometric constraints in the process of attitude maneuver of spacecraft. By the application of this algorithm, the security of certain optical instruments, which is critical in an autonomous system, can be further assured.

Details

Aircraft Engineering and Aerospace Technology, vol. 83 no. 5
Type: Research Article
ISSN: 0002-2667

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Article
Publication date: 31 July 2021

Shifa Sulaiman and A.P. Sudheer

Most of the redundant dual-arm robots are singular free, dexterous and collision free compared to other robotic arms. This paper aims to analyse the workspace of redundant…

Abstract

Purpose

Most of the redundant dual-arm robots are singular free, dexterous and collision free compared to other robotic arms. This paper aims to analyse the workspace of redundant arms to study the manipulability. Furthermore, multi-layer perceptron (MLP) algorithm is used to determine the various joint parameters of both the upper body redundant arms. Trajectory planning of robotic arms is carried out with the help of inverse solutions obtained from the MLP algorithm.

Design/methodology/approach

In this paper, the kinematic equations are derived from screw theory approach and inverse kinematic solutions are determined using MLP algorithm. Levenberg–Marquardt (LM) and Bayesian regulation (BR) techniques are used as the backpropagation algorithms. The results from two backpropagation techniques are compared for determining the prediction accuracy. The inverse solutions obtained from the MLP algorithm are then used to optimize the cubic spline trajectories planned for avoiding collision between arms with the help of convex optimization technique. The dexterity of the redundant arms is analysed with the help of Cartesian workspace of arms.

Findings

Dexterity of redundant arms is analysed by studying the voids and singular spaces present inside the workspace of arms. MLP algorithms determine unique solutions with less computational effort using BR backpropagation. The inverse solutions obtained from MLP algorithm effectively optimize the cubic spline trajectory for the redundant dual arms using convex optimization technique.

Originality/value

Most of the MLP algorithms used for determining the inverse solutions are used with LM backpropagation technique. In this paper, BR technique is used as the backpropagation technique. BR technique converges fast with less computational time than LM method. The inverse solutions of arm joints for traversing optimized cubic spline trajectory using convex optimization technique are computed from the MLP algorithm.

Details

Industrial Robot: the international journal of robotics research and application, vol. 48 no. 6
Type: Research Article
ISSN: 0143-991X

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Article
Publication date: 21 August 2017

Kamal Sharma, Varsha Shirwalkar and Prabir K. Pal

This paper aims to provide a solution to the first phase of a force-controlled circular Peg-In-Hole assembly using an industrial robot. The paper suggests motion planning

Abstract

Purpose

This paper aims to provide a solution to the first phase of a force-controlled circular Peg-In-Hole assembly using an industrial robot. The paper suggests motion planning of the robot’s end-effector so as to perform Peg-In-Hole search with minimum a priori information of the working environment.

Design/methodology/approach

The paper models Peg-In-Hole search problem as a problem of finding the minima in depth profile for a particular assembly. Thereafter, various optimization techniques are used to guide the robot to locate minima and complete the hole search. This approach is inspired by a human’s approach of searching a hole by moving peg in various directions so as to search a point of maximum insertion which is same as the minima in depth profile.

Findings

The usage of optimization techniques for hole search allows the robot to work with minimum a priori information of the working environment. Also, the iterative nature of the techniques adapts to any disturbance during assembly.

Practical implications

The techniques discussed here are quite useful if a force-controlled assembly needs to be performed in a highly unknown environment and also when the assembly setup can get disturbed in between.

Originality/value

The concept is original and provides a non-conventional use of optimization techniques, not for optimization of some process directly but for an industrial robot’s motion planning.

Details

Industrial Robot: An International Journal, vol. 44 no. 5
Type: Research Article
ISSN: 0143-991X

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Article
Publication date: 20 March 2017

Thomas Fridolin Iversen and Lars-Peter Ellekilde

For robot motion planning there exists a large number of different algorithms, each appropriate for a certain domain, and the right choice of planner depends on the…

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Abstract

Purpose

For robot motion planning there exists a large number of different algorithms, each appropriate for a certain domain, and the right choice of planner depends on the specific use case. The purpose of this paper is to consider the application of bin picking and benchmark a set of motion planning algorithms to identify which are most suited in the given context.

Design/methodology/approach

The paper presents a selection of motion planning algorithms and defines benchmarks based on three different bin-picking scenarios. The evaluation is done based on a fixed set of tasks, which are planned and executed on a real and a simulated robot.

Findings

The benchmarking shows a clear difference between the planners and generally indicates that algorithms integrating optimization, despite longer planning time, perform better due to a faster execution.

Originality/value

The originality of this work lies in the selected set of planners and the specific choice of application. Most new planners are only compared to existing methods for specific applications chosen to demonstrate the advantages. However, with the specifics of another application, such as bin picking, it is not obvious which planner to choose.

Details

Industrial Robot: An International Journal, vol. 44 no. 2
Type: Research Article
ISSN: 0143-991X

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Article
Publication date: 22 June 2010

Tao Zhang, Yi Zhu and Jingyan Song

The purpose of this paper is to focus on the local minima issue encountered in motion planning by the artificial potential field (APF) method, investigate the currently…

Abstract

Purpose

The purpose of this paper is to focus on the local minima issue encountered in motion planning by the artificial potential field (APF) method, investigate the currently existing approaches and analyze four types of previous methods. Based on the conclusions of analysis, this paper presents an improved wall‐following approach for real‐time application in mobile robots.

Design/methodology/approach

In the proposed method, new switching conditions among various behaviors are reasonably designed in order to guarantee the reliability and the generality of the method. In addition, path memory is incorporated in this method to enhance the robot's cognition capability to the environment. Therefore, the new method greatly weakens the blindness of decision making of robot and it is very helpful to select appropriate behaviors facing to the changeable situation. Comparing with the previous methods which are normally considering specific obstacles, the effectiveness of this proposed method for the environment with convex polygon‐shaped obstacles has been theoretically proved. The simulation and experimental results further demonstrate that the proposed method is adaptable for the environment with convex polygon‐shaped obstacles or non‐convex polygon‐shaped obstacles. It has more widely generality and adaptiveness than other existed methods in complicated unknown environment.

Findings

The proposed method can effectively realize real time motion planning with high reliability and generality. The cognition capability of mobile robot to the environment can be improved in order to adapt to the changeable situation. The proposed method can be suitable to more complex unknown environment. It is more applicable for actual environment comparing with other traditional APF methods.

Originality/value

This paper has widely investigated the currently existed approaches and analyzes deeply on four types of traditional APF methods adopted for real time motion planning in unknown environment with simulation works. Based on the conclusions of analysis, this paper presents an improved wall‐following approach. The proposed method can realize real time motion planning considering more complex environment with high reliability and generality. The simulation and experimental results further demonstrate that the proposed method is adaptable for the environment with convex polygon‐shaped obstacles or non‐convex polygon‐shaped obstacles. It has more widely generality and adaptiveness than other existed methods in complicated unknown environment.

Details

Industrial Robot: An International Journal, vol. 37 no. 4
Type: Research Article
ISSN: 0143-991X

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Article
Publication date: 7 September 2015

Lin Chen, Chongqi Ni, Junjie Feng, Jun Dai, Bingqiong Huang, Huaping Liu and Haihong Pan

This paper aims to find an objects representation scheme with high precision and to compute the objects’ separation distance effectively in final analysis. Proximity…

Abstract

Purpose

This paper aims to find an objects representation scheme with high precision and to compute the objects’ separation distance effectively in final analysis. Proximity queries have been used widely in robot trajectory planning, automatic assembly planning, virtual surgery and many other applications. The core of proximity query is the precise computation of (minimum) separation distance in narrow phase, and specific object representation scheme corresponds to different methods of separation distance computation.

Design/methodology/approach

In this paper, a second-order cone programming (SOCP)-based (minimum) separation distance computation algorithm was proposed. It treats convex superquadrics, descriptive primitives of complex object as the study objects. The separation distance between two convex superquadrics was written as a general nonlinear programming (NLP) problem with superquadric constraints and then transformed into an SOCP problem with the method of conic formulation of superquadric constraints. Finally, a primal-dual interior point method embedded in MOSEK was used for solving the SOCP problem.

Findings

The proposed algorithm achieved exact separation distance computation between convex superquadrics, with a relative error of 10-6. It is particularly suitable for proximity queries in narrow phase of static collision detection algorithms. Further, the proposed algorithm achieved continuous collision detection between rectilinear translation superquadrics.

Originality/value

The proposed algorithm in narrow phase of static collision detection algorithms makes objects’ separation distance effectively computed. Proximity queries are easy and more accurate to perform in this way.

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Article
Publication date: 23 February 2010

Chen Zhou and Yuehong Yin

The purpose of this paper is to develop a computationally efficient and generally applicable measure for a pipe routing problem which decides the pipe paths and affects…

Abstract

Purpose

The purpose of this paper is to develop a computationally efficient and generally applicable measure for a pipe routing problem which decides the pipe paths and affects the pipe assembly feasibility. By imitating human thinking in pipe assembly planning, human's experience and intuition are quantified and applied in the pipe routing algorithm.

Design/methodology/approach

Human's imaginal thinking is simulated with procedures of knowledge representation, pattern recognition, and logical deduction; the algorithm transforms the physical obstacles and constraints into 3D pipe routing space and then into 2D planar projection, by using convex hull algorithm onto the projection, the shortest pipe route is found efficiently.

Findings

A novel pipe assembly planning algorithm by imitating human imaginal thinking is presented, which effectively solved the problem of conceiving the shortest pipe route in 3D space with obstacles and constraints.

Practical implications

The application of the algorithm in assembly planning of an aircraft engine pipe system is demonstrated. The algorithm can also be used in similar pipe planning problems such as industrial plant pipe planning and submarine pipe system design.

Originality/value

Human's imaginal thinking is introduced into pipe routing algorithm for the first time. By using graphics as the media to transfer the pipe routing information, human's experience and intuition in pipe assembly planning are quantified and computationally applicable.

Details

Assembly Automation, vol. 30 no. 1
Type: Research Article
ISSN: 0144-5154

Keywords

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Article
Publication date: 1 December 1999

Yong Yue, J.L. Murray, J.R. Corney and D.E.R. Clark

The problem of constructing the convex hull of a set of points and of curvilinear segments arises in many applications of geometric analysis. Although there has been much…

Abstract

The problem of constructing the convex hull of a set of points and of curvilinear segments arises in many applications of geometric analysis. Although there has been much work on algorithms for the convex hull of a finite point set, there has been less on methods for dealing with circular line segments and the implementation issues. This paper describes a new method for finding the convex hull of a planar set of straight and circular line segments. It then concentrates on the implementation of the algorithm.

Details

Engineering Computations, vol. 16 no. 8
Type: Research Article
ISSN: 0264-4401

Keywords

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Article
Publication date: 3 June 2014

Mahsan Esmaeilzadeh Tarei, Bijan Abdollahi and Mohammad Nakhaei

The purpose of this paper is to describe imperialist competitive algorithm (ICA), a novel socio-politically inspired optimization strategy for proposing a fuzzy variant of…

Abstract

Purpose

The purpose of this paper is to describe imperialist competitive algorithm (ICA), a novel socio-politically inspired optimization strategy for proposing a fuzzy variant of this algorithm. ICA is a meta-heuristic algorithm for dealing with different optimization tasks. The basis of the algorithm is inspired by imperialistic competition. It attempts to present the social policy of imperialisms (referred to empires) to control more countries (referred to colonies) and use their sources. If one empire loses its power, among the others making a competition to take possession of it.

Design/methodology/approach

In fuzzy imperialist competitive algorithm (FICA), the colonies have a degree of belonging to their imperialists and the top imperialist, as in fuzzy logic, rather than belonging completely to just one empire therefore the colonies move toward the superior empire and their relevant empires. Simultaneously for balancing the exploration and exploitation abilities of the ICA. The algorithms are used for optimization have shortcoming to deal with accuracy rate and local optimum trap and they need complex tuning procedures. FICA is proposed a way for optimizing convex function with high accuracy and avoiding to trap in local optima rather than using original ICA algorithm by implementing fuzzy logic on it.

Findings

Therefore several solution procedures, including ICA, FICA, genetic algorithm, particle swarm optimization, tabu search and simulated annealing optimization algorithm are considered. Finally numerical experiments are carried out to evaluate the effectiveness of models as well as solution procedures. Test results present the suitability of the proposed fuzzy ICA for convex functions with little fluctuations.

Originality/value

The proposed evolutionary algorithm, FICA, can be used in diverse areas of optimization problems where convex functions properties are appeared including, industrial planning, resource allocation, scheduling, decision making, pattern recognition and machine learning (optimization techniques; fuzzy logic; convex functions).

Details

International Journal of Intelligent Computing and Cybernetics, vol. 7 no. 2
Type: Research Article
ISSN: 1756-378X

Keywords

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Article
Publication date: 3 December 2019

R. Ghasemy Yaghin and P. Sarlak

This paper aims to propose an integrated supplier selection, order allocation, transportation planning model, along with investment planning for corporate social…

Abstract

Purpose

This paper aims to propose an integrated supplier selection, order allocation, transportation planning model, along with investment planning for corporate social responsibility (CSR), over a given multi-period horizon under uncertainty. Furthermore, a customer’s behavior to pay more money for items with CSR attributes is considered in the total market demand.

Design/methodology/approach

The objective functions, i.e. social value of purchasing, total profit (TP), total delivery lead-time, total air pollution, total water pollution and total energy consumption with regard to a number of constraints are jointly considered in a multi-product system. It is worth noting that operational- and sustainable-related parameters are usually vague and imprecise in this area. Therefore, this paper develops a new fuzzy multi-objective optimization model to capture this inherent fuzziness in critical data.

Findings

Through the numerical examples in the textile industry, the application of the model and usefulness of solution procedures are carried out. The numerical results obtained from the proposed approach indicate the efficiency of the solution algorithm in different instances. Moreover, the authors observe that social investment of the buyer, to stimulate market demand, can affect the TP and also involve the total contribution of suppliers in social responsibility.

Originality/value

This research work concentrates on providing a procurement and inventory model through the lens of sustainability to enable textile supply chain managers and related industries to apply the approach to their inventory control and supply management. Totally, the proposed methodology could be applied by many fabric buyers of textile industry tackling purchasing issues and attempting to perfect understanding of social supply chains.

Details

Journal of Modelling in Management, vol. 15 no. 2
Type: Research Article
ISSN: 1746-5664

Keywords

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