Robotic collision avoidance in a flexible assembly cell using a dynamic knowledge base

Manivannan, S.

doi:10.1109/21.256548

Cited by 11 publications

(7 citation statements)

References 26 publications

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“…According to the equation (1), it can be seen that the rule i with minimum value of objective function k has a normalised value of 1 and the rule i with maximum value of objective function k has a normalised value equal to 0.…”

Section: Normalisation Of the Objective Valuesmentioning

confidence: 99%

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Application of Fuzzy Logic to Multi-Objective Scheduling Problems in Robotic Flexible Assembly Cells

Abd¹,

Abhary²,

Marian³

2013

ACIS

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This paper is aimed at developing a methodology to solve a multi-objective problem in robotic flexible assembly cells. The proposed methodology is based on three main steps: (1) scheduling of the RFACs using different common rules, (2) normalisation of the scheduling outcomes, and (3) selection of the optimal scheduling rules, using a fuzzy inference system. In this paper, four rules, namely short processing time, long processing time, earlier due date and random, are examined. Four objectives are considered simultaneously: scheduling length, total transportation time, utilisation rate and workload rate. A realistic case study is provided for demonstrating applicability of the suggested methodology. The results show that the methodology is practical and works in RFACs settings.

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Section: Normalisation Of the Objective Valuesmentioning

confidence: 99%

“…One class of such systems is called robotic flexible assembly cells (RFACs). RFACs are highly modern systems, structured with industrial robot(s), assembly stations and an automated material handling system, all monitored by computer numerical control [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

Application of Fuzzy Logic to Multi-Objective Scheduling Problems in Robotic Flexible Assembly Cells

Abd¹,

Abhary²,

Marian³

2013

ACIS

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“…Studies in robotic collision avoidance have existed for many years [2], [3], [4]. Robots need to be able to find their own way to their destination as well as to avoid obstacles on their path.…”

Section: Robotic Collision Avoidancementioning

confidence: 99%

U&I Aware: A Framework Using Data Mining and Collision Detection to Increase Awareness for Intersection Users

Salim

Loke

Rakotonirainy³

et al. 2007

21st International Conference on Advanced Information Networking and Applications Workshops (AINAW'07)

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An intersection safety system should adapt to the particular characteristics that identify an intersection, by mining traffic and collision data. Given the large amount of sensor data that are obtained for intersections and from sensor-equipped cars, analysis and learning of such data is essential. This paper presents a new method to improve safety at intersections using a combination of a mathematical based collision detection algorithm and data mining. A number of scenarios at a simulated intersection are explored with encouraging results from our data mining implementation. The results suggest that our approach can help improve situation awareness and automate understanding of intersections, which, in turn, can be used to increase safety at intersections.

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“…One of these systems is called robotic fl exible assembly cells (RFACs). This system is a highly modern concept, structured with industrial robot(s), assembly stations and an automated material handling system, all monitored by computer numerical control (Manivannan, 1993;Marian et al, 2003;Sawik, 1999). The design of RFACs with more than one robot offer many advantages over single robot.…”

Section: Introductionmentioning

confidence: 99%

A fuzzy decision support system for selecting the optimal scheduling rule in robotic flexible assembly cells

Abd¹,

Abhary²,

Marian³

2013

AJMDE

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The aim of this paper is to present a proposed methodology to select optimal scheduling rule for robotic fl exible assembly cells based fuzzy decision support system. Six common scheduling rules are considered, and three independent objectives, namely, the minimising of makespan (C max ), total tardiness (TD) and percentage of tardy jobs (%T) are measured. A fuzzy decision support system is implemented using the Matlab fuzzy toolbox. The fi nal results demonstrate the effectiveness of the proposed methodology to select optimal scheduling rule in a multi-product assembly environment.

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Robotic collision avoidance in a flexible assembly cell using a dynamic knowledge base

Cited by 11 publications

References 26 publications

Application of Fuzzy Logic to Multi-Objective Scheduling Problems in Robotic Flexible Assembly Cells

Application of Fuzzy Logic to Multi-Objective Scheduling Problems in Robotic Flexible Assembly Cells

U&I Aware: A Framework Using Data Mining and Collision Detection to Increase Awareness for Intersection Users

A fuzzy decision support system for selecting the optimal scheduling rule in robotic flexible assembly cells

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