Thesis etd-04132023-095844 |
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Thesis type
Tesi di laurea magistrale
URN
etd-04132023-095844
Thesis title
Implementing x-ray vision as a support tool for unmanned vehicle piloting using augmented reality
Department
INGEGNERIA DELL'INFORMAZIONE
Course of study
INGEGNERIA ROBOTICA E DELL'AUTOMAZIONE
Supervisors
.
relatore Prof. Pollini, Lorenzo
Keywords
- augmented reality
- calibration
- LiDAR
- Quest 2
- remote site exploration
- see-through vision
- situational awareness
- x-ray vision
Graduation session start date
04/05/2023
Availability
Withheld
Release date
04/05/2093
Abstract (Inglese)
Abstract (Italiano)
This thesis presents the development of an innovative support system that aims to improve situational awareness during inaccessible site exploration using unmanned vehicles equipped with sensors. The system leverages augmented reality techniques to enable the operator to see the avatar's vehicle through obstacles as if they were semi-transparent reducing the risk of spatial disorientation for the pilot, which can lead to mistakes in maneuvering the vehicle and increase the risk of accidents or collisions with obstacles.
The first phase of the work involves the calibration process to align the reference frame of the real world with the one of the virtual world, in order to ensure consistency in the reproduction of the vehicle’s motions and of the physical features of the environment onto the Oculus Quest 2 display. In particular, an optimization process for the calibration procedure is designed to adapt the system in large-scale environments. Calibration methods are then assessed with validation data.
Subsequently, the system uses LiDAR technology to show depth data in augmented reality, allowing for the creation of virtual objects that determine the shape of the explored scenario. An evaluation of how this proposed AR interface affects situational awareness has been made by simulating an indoor inspection task.
The first phase of the work involves the calibration process to align the reference frame of the real world with the one of the virtual world, in order to ensure consistency in the reproduction of the vehicle’s motions and of the physical features of the environment onto the Oculus Quest 2 display. In particular, an optimization process for the calibration procedure is designed to adapt the system in large-scale environments. Calibration methods are then assessed with validation data.
Subsequently, the system uses LiDAR technology to show depth data in augmented reality, allowing for the creation of virtual objects that determine the shape of the explored scenario. An evaluation of how this proposed AR interface affects situational awareness has been made by simulating an indoor inspection task.
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