Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/3042
Full metadata record
DC FieldValueLanguage
dc.contributor.authorDeepak, BBVL-
dc.contributor.authorParhi, D R-
dc.date.accessioned2018-08-07T12:05:16Z-
dc.date.available2018-08-07T12:05:16Z-
dc.date.issued2018-07-
dc.identifier.citation5th International Conference on information system design and intelligent applications, Mauritius, Mauritius, 19-21 July, 2018en_US
dc.identifier.urihttp://hdl.handle.net/2080/3042-
dc.descriptionCopyright of this article is with proceedings publisher.en_US
dc.description.abstractThis paper deals with the development of an efficient Fuzzy Inference System (FIS) based architecture for mobile robot navigation. While developing the system architecture, kinematic constraints have been considered for a differential drive mobile robot. During the analysis, robot chassis is considered as a rigid body and the position of the mobile robot is represented as a point in XY- plane. The developed kinematic models are useful to find out the robot’s velocities (X-direction, Y-direction & angular). The proposed fuzzy model requires two inputs: (1) the distance between the robot and the obstacles in the environment and (2) position of the target i.e. the robot heading angle towards the destination. Once the system gets the knowledge from the environment, it will obtain the suitable steering angle for an autonomous mobile robot. This process will be continued until the robot reaches its goal. Simulation and experimental results are presented to verify the effectiveness of the proposed methodology for an autonomous mobile robot.en_US
dc.subjectDesign For Assemblyen_US
dc.subjectAssembly Sequence Planningen_US
dc.subjectAssembly Constraintsen_US
dc.subjectFirefly Algorithmen_US
dc.subjectComputer Aided Design (CAD)en_US
dc.titlePath Generation of a Differential Mobile Robot Using Fuzzy Inference systemen_US
dc.typeArticleen_US
Appears in Collections:Conference Papers

Files in This Item:
File Description SizeFormat 
2018_ICISDIA_BBVLDeepak_Pathgeneration.pdfConference paper698.55 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.