MAR-CPS: Measurable Augmented Reality for Prototyping Cyber-Physical Systems
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3.09 MB
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Checksum (MD5)
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Author(s)
Vian, John L.
Surati, Rajeev
Omidshafiei, Shayegan
Aghamohammadi, Aliakbar
Chen, Yu Fan
Ure, Nazim Kemal
How, Jonathan P
Date Issued
January 2015
Journal
AIAA Infotech @ Aerospace
Publisher
American Institute of Aeronautics and Astronautics (AIAA)
Citation
Omidshafiei, Shayegan, et al. "MAR-CPS: Measurable Augmented Reality for Prototyping Cyber-Physical Systems." AIAA Infotech @ Aerospace, AIAA SciTech Forum, 5-9 January, 2015, Kissimmee, Florida, American Institute of Aeronautics and Astronautics, 2015.
Version
Author's final manuscript
Abstract
Cyber-Physical Systems (CPSs) refer to engineering platforms that rely on the inte- gration of physical systems with control, computation, and communication technologies. Autonomous vehicles are instances of CPSs that are rapidly growing with applications in many domains. Due to the integration of physical systems with computational sens- ing, planning, and learning in CPSs, hardware-in-the-loop experiments are an essential step for transitioning from simulations to real-world experiments. This paper proposes an architecture for rapid prototyping of CPSs that has been developed in the Aerospace Controls Laboratory at the Massachusetts Institute of Technology. This system, referred to as MAR-CPS (Measurable Augmented Reality for Prototyping Cyber-Physical Systems), includes physical vehicles and sensors, a motion capture technology, a projection system, and a communication network. The role of the projection system is to augment a physical laboratory space with 1) autonomous vehicles' beliefs and 2) a simulated mission environ- ment, which in turn will be measured by physical sensors on the vehicles. The main focus of this method is on rapid design of planning, perception, and learning algorithms for au- tonomous single-agent or multi-agent systems. Moreover, the proposed architecture allows researchers to project a simulated counterpart of outdoor environments in a controlled, indoor space, which can be crucial when testing in outdoor environments is disfavored due to safety, regulatory, or monetary concerns. We discuss the issues related to the design and implementation of MAR-CPS and demonstrate its real-time behavior in a variety of problems in autonomy, such as motion planning, multi-robot coordination, and learning spatio-temporal fields.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.2514/6.2015-0643
