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Event-Based Perception for Ground Vehicle Control / Kendall J Queen.
- Format:
- Book
- Thesis/Dissertation
- Author/Creator:
- Queen, Kendall J., author.
- Language:
- English
- Subjects (All):
- Robotics.
- Information technology.
- Electrical engineering.
- Electrical and Systems Engineering--Penn dissertations.
- Penn dissertations--Electrical and Systems Engineering.
- Local Subjects:
- Robotics.
- Information technology.
- Electrical engineering.
- Electrical and Systems Engineering--Penn dissertations.
- Penn dissertations--Electrical and Systems Engineering.
- Physical Description:
- 1 online resource (195 pages)
- Contained In:
- Dissertations Abstracts International 85-03B.
- Place of Publication:
- [Philadelphia, Pennsylvania] : University of Pennsylvania, 2022.
- Ann Arbor : ProQuest Dissertations & Theses, 2023
- Language Note:
- English
- Summary:
- Autonomous vehicles rely on environmental perception to inform the system on how to act. Vision sensors, such as conventional cameras, have been at the forefront of the perception of most mobile platforms. However, conventional cameras have limitations such as high data rates, low dynamic range, and high latency. Dynamic vision sensors, such as event cameras, address and overcome those shortcomings by recording changes in the logarithm of light intensity at pixel level asynchronously and independently. With the benefits of high dynamic range, low power consumption, low latency, and high temporal resolution, event cameras excel as vision sensors for autonomous ground vehicle applications. This dissertation highlights the use of event cameras to inform control decisions for autonomous ground vehicles. Additionally, it introduces a new 1/10th scale autonomous testing platform, Ryder. Ryder is used to demonstrate real-time event informed control.
- Notes:
- Source: Dissertations Abstracts International, Volume: 85-03, Section: B.
- Advisors: Daniilidis, Kostas; Matni, Nikolai; Committee members: Koditscheck, Daniel; Taylor, Camillo J.; Kumar, Vijay.
- Department: Electrical and Systems Engineering.
- Ph.D. University of Pennsylvania 2023.
- Local Notes:
- School code: 0175
- ISBN:
- 9798380387903
- Access Restriction:
- Restricted for use by site license.
- This item is not available from ProQuest Dissertations & Theses.
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