TY - GEN
T1 - Go-CHART
T2 - 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2020
AU - Kannapiran, Shenbagaraj
AU - Berman, Spring
N1 - Funding Information:
This work was supported by the ASU Global Security Initiative.
Publisher Copyright:
© 2020 IEEE.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2020/10/24
Y1 - 2020/10/24
N2 - The Go-CHART is a four-wheel, skid-steer robot that resembles a 1:28 scale standard commercial sedan. It is equipped with an onboard sensor suite and both onboard and external computers that replicate many of the sensing and computation capabilities of a full-size autonomous vehicle. The Go-CHART can autonomously navigate a small-scale traffic testbed, responding to its sensor input with programmed controllers. Alternatively, it can be remotely driven by a user who views the testbed through the robot's four camera feeds, which facilitates safe, controlled experiments on driver interactions with driverless vehicles. We demonstrate the Go-CHART's ability to perform lane tracking and detection of traffic signs, traffic signals, and other Go-CHARTs in real-time, utilizing an external GPU that runs computationally intensive computer vision and deep learning algorithms.
AB - The Go-CHART is a four-wheel, skid-steer robot that resembles a 1:28 scale standard commercial sedan. It is equipped with an onboard sensor suite and both onboard and external computers that replicate many of the sensing and computation capabilities of a full-size autonomous vehicle. The Go-CHART can autonomously navigate a small-scale traffic testbed, responding to its sensor input with programmed controllers. Alternatively, it can be remotely driven by a user who views the testbed through the robot's four camera feeds, which facilitates safe, controlled experiments on driver interactions with driverless vehicles. We demonstrate the Go-CHART's ability to perform lane tracking and detection of traffic signs, traffic signals, and other Go-CHARTs in real-time, utilizing an external GPU that runs computationally intensive computer vision and deep learning algorithms.
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U2 - 10.1109/IROS45743.2020.9341770
DO - 10.1109/IROS45743.2020.9341770
M3 - Conference contribution
AN - SCOPUS:85102406039
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 2265
EP - 2272
BT - 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2020
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 24 October 2020 through 24 January 2021
ER -