Design, Development, and Human Analogous Control of a Climbing Robot

Simple item page
dc.contributor.advisorMehrandezh, Mehran
dc.contributor.advisorDai, Liming
dc.contributor.authorBazargan, Amirhossein
dc.contributor.committeememberAroonwilas, Adisorn
dc.contributor.committeememberMayorga, Rene
dc.contributor.externalexaminerParanjape, Raman
dc.date.accessioned2012-11-13T20:09:22Z
dc.date.available2012-11-13T20:09:22Z
dc.date.issued2012-03
dc.descriptionA Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Master of Applied Science in Industrial Systems Engineering, University of Regina. xvi, 128 l.en_US
dc.description.abstractIn this thesis, a re-configurable wheeled climbing robot has been introduced. This robot is capable of doing a multitude of tasks that no other single robot could do in the past. It can climb staircases, move inside empty ducts and pipes, climb up ropes and poles of varying cross sections, and even jump over obstacles with proper motion coordination. It can also move inside narrow passageways by reconfiguring itself. The design of a re-configurable robot capable of traversing a wide range of unconventional terrains is the novelty in this invention. A comprehensive dynamic model of the robot is derived for the first time. A real-time simulator to try different control strategies by a human operator using conventional human-machine interfaces has been developed. This simulator can be employed to size the electromechanical actuators and to synthesize different control strategies in a short time. The data obtained can be also used to design a human-analogous autonomous controller. After outline of the theory, background and applications of soft computing techniques for system construction and control including Artificial Neural Networks (ANN), Fuzzy Logic Control (FLC), and the Adaptive Neuro-Fuzzy Inference Systems (ANFIS), a novel human-analogous control strategy based on ANFIS was implemented to control the position of the robot climbing a straight pole against gravity. The design process of the ANFIS-based human-analogous control strategy includes the following steps: First, a human expert tries to control the real system in real time within a human-in-the-loop simulator via a Human-Machine Interface (HMI) using sensory information obtained from visual tracing in the HMI in real time from the real system. The control task is done by using a control interface (i.e., a joystick). Relevant input/output data is stored, filtered, and used offline to tune the parameters of an ANFIS-based controller. The ANFIS controller whose parameters have been optimized is then implemented on the real system autonomously. Based on the information obtained via the HITL simulator system, the controller can extrapolate needed data for untrained cases.en_US
dc.description.authorstatusStudenten
dc.description.peerreviewyesen
dc.identifier.tcnumberTC-SRU-3617
dc.identifier.thesisurlhttp://ourspace.uregina.ca/bitstream/handle/10294/3617/Bazargan_Amirhossein_200262946_MASC_ISE_Spring2012.pdf
dc.identifier.urihttps://hdl.handle.net/10294/3617
dc.language.isoenen_US
dc.publisherFaculty of Graduate Studies and Research, University of Reginaen_US
dc.subject.lcshMobile robots
dc.subject.lcshRobots--Control systems
dc.subject.lcshHuman-robot interaction
dc.titleDesign, Development, and Human Analogous Control of a Climbing Roboten_US
dc.typeThesisen
thesis.degree.departmentFaculty of Engineering and Applied Scienceen_US
thesis.degree.disciplineEngineering - Industrial Systemsen_US
thesis.degree.grantorUniversity of Reginaen
thesis.degree.levelMaster'sen
thesis.degree.nameMaster of Applied Science (MASc)en_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Bazargan_Amirhossein_200262946_MASC_ISE_Spring2012.pdf
Size:
1.6 MB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
2.31 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Master's Theses