Return to search

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

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. / Master of Science / 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. Such robots can prove useful in environments that are either too dangerous or inaccessible to humans. Therefore, in this research, several specific hardware and software development aspects related to self-reconfigurable mobile robots are proposed. In terms of hardware development, a robotic module was designed that is symmetrically invertible and exhibits dual mobility using a tracked drive for longitudinal locomotion and wheeled drive for lateral locomotion. Such interchangeable mobility is important when the robot operates in a constrained workspace. The mobile robot also has integrated two degrees of freedom (DOF) docking mechanisms referred to as GHEFT (Genderless, High strength, Efficient, Fail-Safe, high misalignment Tolerant). The docking interface allows for an efficient docking while tolerating misalignments in 6-DOF. In addition, motion along the vertical axis is also performed via an additional translational DOF, allowing for lowering and raising the wheeled assembly. The robot is equipped with sensors to provide positional feedback of the joints relative to the target robot. In terms of software development, a visual-based onboard Hybrid Target Tracking algorithm for high-speed consistent tracking iv of colored targets is also presented in this work. The proposed technique is used to detect and follow a colored target attached to the target robot leading to autonomous docking between the modules using Image Based Visual Servoing (IBVS). Experimental results to validate the robustness of the proposed tracking approach, as well as the reliability of the autonomous docking procedure, are also presented in the thesis. The thesis is concluded with discussions about future research in both structured and unstructured terrains.

Identiferoai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/90889
Date02 July 2019
CreatorsSohal, Shubhdildeep Singh
ContributorsMechanical Engineering, Ben-Tzvi, Pinhas, Furukawa, Tomonari, Wicks, Alfred L.
PublisherVirginia Tech
Source SetsVirginia Tech Theses and Dissertation
Detected LanguageEnglish
TypeThesis
FormatETD, application/pdf
RightsIn Copyright, http://rightsstatements.org/vocab/InC/1.0/

Page generated in 0.023 seconds