FlightGoggles: Photorealistic Sensor Simulation for Perception-driven Robotics using Photogrammetry and Virtual Reality
Name
1905.11377.pdf
Description
Submitted version
Size
9.1 MB
Format
Adobe PDF
Checksum (MD5)
603c08baf6397dd0e10324f9edbe085f
Author(s)
Guerra, Winter
Tal, Ezra
Murali, Varun
Ryou, Gilhyun
Karaman, Sertac
Date Issued
November 2019
Journal
IEEE International Conference on Intelligent Robots and Systems
Publisher
IEEE
Citation
Guerra, Winter, Tal, Ezra, Murali, Varun, Ryou, Gilhyun and Karaman, Sertac. 2019. "FlightGoggles: Photorealistic Sensor Simulation for Perception-driven Robotics using Photogrammetry and Virtual Reality." IEEE International Conference on Intelligent Robots and Systems.
Version
Original manuscript
Abstract
© 2019 IEEE. FlightGoggles is a photorealistic sensor simulator for perception-driven robotic vehicles. The key contributions of FlightGoggles are twofold. First, FlightGoggles provides photorealistic exteroceptive sensor simulation using graphics assets generated with photogrammetry. Second, it provides the ability to combine (i) synthetic exteroceptive measurements generated in silico in real time and (ii) vehicle dynamics and proprioceptive measurements generated in motio by vehicle(s) in flight in a motion-capture facility. FlightGoggles is capable of simulating a virtual-reality environment around autonomous vehicle(s) in flight. While a vehicle is in flight in the Flight-Goggles virtual reality environment, exteroceptive sensors are rendered synthetically in real time while all complex dynamics are generated organically through natural interactions of the vehicle. The FlightGoggles framework allows for researchers to accelerate development by circumventing the need to estimate complex and hard-to-model interactions such as aerodynamics, motor mechanics, battery electrochemistry, and behavior of other agents. The ability to perform vehicle-in-the-loop experiments with photorealistic exteroceptive sensor simulation facilitates novel research directions involving, e.g., fast and agile autonomous flight in obstacle-rich environments, safe human interaction, and flexible sensor selection. FlightGoggles has been utilized as the main test for selecting nine teams that will advance in the AlphaPilot autonomous drone racing challenge. We survey approaches and results from the top AlphaPilot teams, which may be of independent interest. FlightGoggles is distributed as open-source software along with the photorealistic graphics assets for several simulation environments, under the MIT license at http://flightgoggles.mit.edu.
MIT Department
Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/iros40897.2019.8968116
