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Virginia Tech

A Hybrid Tracking Approach for Autonomous Docking in Self-Reconfigurable Robotic Modules

Abstract

dc:description.abstract

Active docking in modular robotic systems has received a lot of interest recently as it allows small versatile robotic systems to coalesce and achieve the structural benefits of larger robotic systems. This feature enables reconfigurable modular robotic systems to bridge the gap between small agile systems and larger robotic systems. The proposed self-reconfigurable mobile robot design exhibits dual mobility using a tracked drive for longitudinal locomotion and wheeled drive for lateral locomotion. The two degrees of freedom (DOF) docking interface referred to as GHEFT (Genderless, High strength, Efficient, Fail-Safe, high misalignment Tolerant) allows for an efficient docking while tolerating misalignments in 6-DOF. In addition, motion along the vertical axis is also achieved via an additional translational DOF, allowing for toggling between tracked and wheeled locomotion modes by lowering and raising the wheeled assembly. This thesis also presents a visual-based onboard Hybrid Target Tracking algorithm to detect and follow a target robot leading to autonomous docking between the modules. As a result of this proposed approach, the tracked features are then used to bring the robots in sufficient proximity for the docking procedure using Image Based Visual Servoing (IBVS) control. Experimental results to validate the robustness of the proposed tracking method, as well as the reliability of the autonomous docking procedure, are also presented in this thesis.

Degree

thesis:*
Name thesis:degree_name
Master of Science
Level thesis:degree_level
masters
Discipline thesis:degree_discipline
Mechanical Engineering
Department dc:contributor.department
Mechanical Engineering
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2019

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Sohal, Shubhdildeep Singh
Chair dc:contributor.committeechair
  • Ben-Tzvi, Pinhas
Committee members dc:contributor.committeemember
  • Furukawa, Tomonari
  • Wicks, Alfred L.

Subjects

dc:subject × 6

Rights

dc:rights
Statement dc:rights
  • In Copyright

Identifiers

dc:identifier.*
Dc Identifier Other
vt_gsexam:21251
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/90889

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Sohal, Shubhdildeep Singh. A Hybrid Tracking Approach for Autonomous Docking in Self-Reconfigurable Robotic Modules. masters thesis, Virginia Tech, 2019. http://hdl.handle.net/10919/90889