A real-time task-oriented scheduling algorithm for distributed multi-robot systems

2004 ◽  
Author(s):  
P. Yuan ◽  
M. Moallem ◽  
R.V. Patel
Keyword(s):  
Real Time ◽  
Scheduling Algorithm ◽  
Time Task ◽  
Robot Systems ◽  
Task Oriented ◽  
Multi Robot

MCSA: A Multi-constraint Scheduling Algorithm for Real-time Task in Virtualized Cloud

2018 ◽  
Author(s):  
Sampa Sahoo ◽  
Ankit Pattanayak ◽  
Kshira Sagar Sahoo ◽  
Bibhudatta Sahoo ◽  
Ashok Kumar Turuk
Keyword(s):  
Real Time ◽  
Scheduling Algorithm ◽  
Time Task

scholarly journals Digital Twin and Virtual Reality Based Methodology for Multi-Robot Manufacturing Cell Commissioning

2020 ◽  
Vol 10 (10) ◽  
pp. 3633
Author(s):  
Luis Pérez ◽  
Silvia Rodríguez-Jiménez ◽  
Nuria Rodríguez ◽  
Rubén Usamentiaga ◽  
Daniel F. García
Keyword(s):  
Virtual Reality ◽  
Real Time ◽  
Manufacturing Process ◽  
Manufacturing Industry ◽  
Feasibility Studies ◽  
Real Time Monitoring ◽  
Digital Twin ◽  
Robot Systems ◽  
Virtual Testbed ◽  
Multi Robot

Intelligent automation, including robotics, is one of the current trends in the manufacturing industry in the context of “Industry 4.0”, where cyber-physical systems control the production at automated or semi-automated factories. Robots are perfect substitutes for a skilled workforce for some repeatable, general, and strategically-important tasks. However, this transformation is not always feasible and immediate, since certain technologies do not provide the required degree of flexibility. The introduction of collaborative robots in the industry permits the combination of the advantages of manual and automated production. In some processes, it is necessary to incorporate robots from different manufacturers, thus the design of these multi-robot systems is crucial to guarantee the maximum quality and efficiency. In this context, this paper presents a novel methodology for process automation design, enhanced implementation, and real-time monitoring in operation based on creating a digital twin of the manufacturing process with an immersive virtual reality interface to be used as a virtual testbed before the physical implementation. Moreover, it can be efficiently used for operator training, real-time monitoring, and feasibility studies of future optimizations. It has been validated in a use case which provides a solution for an assembly manufacturing process.

GENETIC ALGORITHM WITH TWO OBJECTIVE FOR REAL-TIME TASK SCHEDULING WITH COMMUNICATION TIME

2018 ◽  
Vol 6 (1) ◽  
pp. 14-17
Author(s):  
Myungryun Yoo ◽  
Takanori Yokoyama
Keyword(s):  
Real Time ◽  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Multiprocessor System ◽  
Time Task ◽  
Communication Time ◽  
Adaptive Weight ◽  
Np Hard Problem ◽  
Heuristics Algorithm ◽  
Execution Order

Purpose of the study:The real-time task scheduling on multiprocessor system is known as an NP-hard problem. This paper proposes a new real-time task scheduling algorithmwhich considers the communication time between processors and the execution order between tasks. Methodology:Genetic Algorithm (GA)with Adaptive Weight Approach (AWA) is used in our approach. Main Findings:Our approach has two objectives. The first objective is to minimize the total amount of deadline-miss. And the second objective is to minimize the total number of processors used. Applications of this study:For two objectives,the range of each objective is readjusted through Adaptive Weight Approach (AWA) and more useful result is obtained. Novelty/Originality of this study:This study never been done before.This study also wasprovided current information about scheduling algorithm and heuristics algorithm.

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