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Hybrid genetic algorithms for energy efficient path placement of a 6 dof robot manipulator
KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
2016 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

The performance of a manipulator during the execution of a task depends, among other things, on the position of the task inside the robot’s working envelope. When a task can be performed in different locations, depending on the position chosen the solution to the inverse kinematics problem will be different. Thus, by judiciously placing the robot and the given path in the workstation, it is possible to improve its behavior. This project deals with the optimal path placementin order to reduce the overall energy consumption for a 6-dof industrial manipulator. A framework for the visualization of the consumption in the working envelope is proposed and described. Genetic algorithms (GA) are chosen to solve the optimization problem, and the advantages they bring are also described. The proposed approach tries to merge the GA approach with a "brute-force" solution, which is also described. Finally, the goodness of the framework is assessed by comparison of the result with simulations performed with RobotStudioTM.

Abstract [sv]

Prestandan av en manipulator under utförandet av en uppgift beror, bland annat, på positionen av uppgiften inuti robotens arbetsområde. När en uppgift kan utföras på olika platser, beroende på positionen valt lösningen på omvänd kinematikproblemet kommer att vara annorlunda. Således, genom att omdömesgillt placera roboten och given väg i arbetsstationen, är det möjligt att förbättra sitt beteende. Detta projekt handlar om optimala vägen placering i syfte att minska den totala energiförbrukningen för en 6-DOF industriell robot. Ett ramverk för visualisering av förbrukningen i arbets kuvert föreslås och beskrivs. Genetiska algoritmer (GA) är valda för att lösa optimeringsproblemet, och de fördelar de få beskrivs också. De föreslagna strategin försöker sammanfoga GA strategi med en"brute-force" lösning, som också beskrivs. Slutligen är godheten i ramen bedömas genom jämförelse av resultatet med simuleringar utförda med RobotStudio.

Place, publisher, year, edition, pages
2016. , p. 75
Series
Degree Project in Production Engineering, Second Level ; 693
National Category
Mechanical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-198150OAI: oai:DiVA.org:kth-198150DiVA, id: diva2:1055797
Supervisors
Examiners
Available from: 2016-12-13 Created: 2016-12-13 Last updated: 2016-12-13Bibliographically approved

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CiteExportLink to record
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