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dc.coverage.spatialAn approach to reduce computational effort in multiobjective path planning and task allocation for multi robot systems
dc.date.accessioned2023-04-21T16:53:22Z-
dc.date.available2023-04-21T16:53:22Z-
dc.identifier.urihttp://hdl.handle.net/10603/478650-
dc.description.abstractIn today s modern automated and semi-automated sectors, multi-objective path planning algorithms for mobile robot applications are in high demand. Multi-objective optimization algorithms require a more significant amount of computational effort to produce an optimal path. The proposed grid-based multi-objective global path planning algorithm [Quadrant selection algorithm (QSA)] plans the path from the initial location to the target location by considering the direction of movements from the starting position to the target position while requiring the least amount of computation. The direction of movements is divided into quadrants as the primary classification in this method. The created feasible paths are evaluated based on the cumulative path distance travelled in obstacle avoidance. The cumulative angle turned to achieve an ideal path to avoid obstacles. Finally, to make navigation easier for the robot, the ideal path is further smoothed to prevent sharp curves and reduce the distance travelled. The suggested QSA, taken as a whole, decreases the need to seek paths in other quadrants that are unnecessary. The newly designed algorithm is evaluated in various contexts and compared to current algorithms based on the number of cells examined to find the shortest path to the goal. In contrast to existing algorithms, the suggested QSA provides an optimal path by drastically lowering the number of cells examined throughout the computation. The experimental verification of the suggested QSA demonstrates that the approach is feasible in terms of cost and time. newlineIn deploying multiple robots, allocating tasks with the lowest path cost is one of the most frequently encountered difficulties. Our research tackles the multi-robot task allocation problem with the lowest path costs, the minimum computing time, and the most equitable task distribution. newline
dc.format.extentxx,136p.
dc.languageEnglish
dc.relationP.123-135
dc.rightsuniversity
dc.titleAn approach to reduce computational effort in multiobjective path planning and task allocation for multi robot systems
dc.title.alternative
dc.creator.researcherRajchandar, K
dc.subject.keywordEngineering and Technology
dc.subject.keywordEngineering
dc.subject.keywordEngineering Mechanical
dc.subject.keywordcomputational effort
dc.subject.keywordmulti objective path
dc.subject.keywordmulti robot systems
dc.description.note
dc.contributor.guideBaskaran, R
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Mechanical Engineering
dc.date.registered
dc.date.completed2022
dc.date.awarded2022
dc.format.dimensions21cm.
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Mechanical Engineering

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01_title.pdfAttached File28.45 kBAdobe PDFView/Open
02_prelim pages.pdf2.73 MBAdobe PDFView/Open
03_content.pdf28.51 kBAdobe PDFView/Open
04_abstract.pdf60.6 kBAdobe PDFView/Open
05_chapter 1.pdf150.42 kBAdobe PDFView/Open
06_chapter 2.pdf160.42 kBAdobe PDFView/Open
07_chapter 3.pdf589.69 kBAdobe PDFView/Open
08_chapter 4.pdf892.93 kBAdobe PDFView/Open
09_chapter 5.pdf1.1 MBAdobe PDFView/Open
10_chapter 6.pdf1.36 MBAdobe PDFView/Open
11_chapter 7.pdf634.17 kBAdobe PDFView/Open
12_annexures.pdf125.96 kBAdobe PDFView/Open
80_recommendation.pdf87.32 kBAdobe PDFView/Open


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