Modular robot system configuration design based on axiomatic design

2009 ◽  
Author(s):  
Liu Xuan ◽  
Zhang Minglu ◽  
Liu Wei ◽  
Fan Lina
Keyword(s):  
Axiomatic Design ◽  
Configuration Design ◽  
System Configuration ◽  
Modular Robot ◽  
Robot System

scholarly journals Simulation and Analysis of Self-Replicating Robot Decision-Making Systems

Computers ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 9
Author(s):  
Andrew Jones ◽  
Jeremy Straub
Keyword(s):  
Lower Risk ◽  
System Construction ◽  
System Configuration ◽  
Operating Environment ◽  
Robot System ◽  
Robotic Exploration ◽  
Mission Success ◽  
Robot Systems ◽  
System Configurations

Self-replicating robot systems (SRRSs) are a new prospective paradigm for robotic exploration. They can potentially facilitate lower mission costs and enhance mission capabilities by allowing some materials, which are needed for robotic system construction, to be collected in situ and used for robot fabrication. The use of a self-replicating robot system can potentially lower risk aversion, due to the ability to potentially replenish lost or damaged robots, and may increase the likelihood of mission success. This paper proposes and compares system configurations of an SRRS. A simulation system was designed and is used to model how an SRRS performs based on its system configuration, attributes, and operating environment. Experiments were conducted using this simulation and the results are presented.

On the Analysis of a Multi-task Modular Robot System for Field Robotics

2010 ◽  
Author(s):  
Jose Baca ◽  
Manuel Ferre ◽  
Alexandre Campos ◽  
Jose Fernandez ◽  
Rafael Aracil
Keyword(s):  
Modular Robot ◽  
Robot System ◽  
Field Robotics

Assembly System Configuration Design for Reconfigurability Under Uncertain Production Evolution

2019 ◽  
Vol 141 (7) ◽  
Author(s):  
Zhengqian Jiang ◽  
Hui Wang ◽  
Maxim A. Dulebenets ◽  
Junayed Pasha
Keyword(s):  
System Throughput ◽  
Assembly System ◽  
Configuration Design ◽  
System Configuration ◽  
Case Scenario ◽  
Worst Case ◽  
Design Evolution ◽  
Product Evolution ◽  
Concurrent Optimization ◽  
The Impact

Assembly system configuration determines the topological arrangement of stations with defined logical material flow among them. The design of assembly system configuration involves (1) subassembly planning that defines subassembly tasks and between-task material flows and (2) workload balancing that determines the task-station assignments. The assembly system configuration should be flexibly changed and updated to cope with product design evolution and updating. However, the uncertainty in future product evolution poses significant challenges to the assembly system configuration design since the higher cost can be incurred if the assembly line suitable for future products is very different from that for the current products. The major challenges include (1) the estimation of reconfiguration cost, (2) unavailability of probability values for possible scenarios of product evolution, and (3) consideration of the impact of the subassembly planning on the task-station assignments. To address these challenges, this paper formulates a concurrent optimization problem to design the assembly system configuration by jointly determining the subassembly planning and task-station assignments considering uncertain product evolution. A new assembly hierarchy similarity model is proposed to estimate the reconfiguration effort by comparing the commonalities among different subassembly plans of current and potential future product designs. The assembly system configuration is chosen by maximizing both assembly hierarchy similarity and assembly system throughput under the worst-case scenario. A case study motivated by real-world scenarios demonstrates the applicability of the proposed method including scenario analysis.

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