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Virginia Tech

Remote Operator Blended Intelligence System for Environmental Navigation and Discernment (RobiSEND)

Abstract

dc:description.abstract

Mini Rotorcraft Unmanned Aerial Vehicles (MRUAVs) flown at low altitude as a part of a human-robot team are potential sources of tactical information for local search missions. Traditionally, their effectiveness in this role has been limited by an inability to intelligently perceive unknown environments or integrate with human team members. Human-robot collaboration provides the theory for building cooperative relationships in this context. This theory, however, only addresses those human-robot teams that are either robot-centered or human-centered in their decision making processes or relationships. This work establishes a new branch of human-robot collaborative theory, Operator Blending, which creates codependent and cooperative relationships between a single robot and human team member for tactical missions. Joint Intension Theory is the basis of this approach, which allows both the human and robot to contribute what each does well in accomplishing the mission objectives. Information processing methods for shared visual information and object tracking take advantage of the human role in the perception process. In addition, coupling of translational commands and the search process establish navigation as the shared basis of communication between the MRUAV and human, for system integration purposes. Observation models relevant to both human and robotic collaborators are tracked through a boundary based approach deemed AIM-SHIFT. A system is developed to classify the semantic and functional relevance of an observation model to local search called the Code of Observational Genetics (COG). These COGs are used to qualitatively map the environment through Qualitative Unsupervised Intelligent Collaborative Keypoint (QUICK) mapping, created to support these methods.

Degree

thesis:*
Name thesis:degree_name
Ph. D.
Level thesis:degree_level
doctoral
Discipline thesis:degree_discipline
Mechanical Engineering
Department dc:contributor.department
Mechanical Engineering
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2011

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Gaines, Jonathan Elliot
Chair dc:contributor.committeechair
  • Wicks, Alfred L.
Committee members dc:contributor.committeemember
  • Woolsey, Craig A.
  • Kurdila, Andrew J.
  • Xuan, Jianhua Jason
  • Kochersberger, Kevin B.

Subjects

dc:subject × 8

Rights

dc:rights
Statement dc:rights
  • In Copyright

Identifiers

dc:identifier.*
Dc Identifier Other
etd-09192011-195545
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/29032

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

Gaines, Jonathan Elliot. Remote Operator Blended Intelligence System for Environmental Navigation and Discernment (RobiSEND). doctoral thesis, Virginia Tech, 2011. http://hdl.handle.net/10919/29032