Motion Estimation of Autonomous Vehicle in Noisy Surroundings Using Kalman Filter-Reference-Cited by-同舟云学术

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Motion Estimation of Autonomous Vehicle in Noisy Surroundings Using Kalman Filter

Published:2020 Issue: Volume: Page:65-75
ISSN:1876-1100
Container-title:Lecture Notes in Electrical Engineering
language:
Short-container-title:

Author:

Jain Ankur,Roy B. K.

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-15-4676-1_6

Reference35 articles.

1. Besselink B, turri V, Van De Hoef SH, Liang K-Y, Alam J, Johansson KH, (2016) Cyber-physical control of road freight transport. Proc IEEE 104(5):1128–1141

2. Thrun S, Montemerlo M, Dahlkamp H, Stavens D, Aron A, Diebel J, Fong P, Gale J, Halpenny M, Hoffmann G et al (2006) Stanley: the robot that won the DARPA Grand Challenge. J Field Robot 23(9):661–692

3. Nemeth B, Csikos A, Varga I, Gaspar P (2012) Road inclinations and emissions in platoon control via multi-criteria optimization. In: 2012 20th Mediterranean conference on control and automation, MED 2012—conference proceedings, pp 1524–1529

4. Jain A, Roy BK (2018) Tradeoff between quality of control (QoC) and quality of service (QoS) for networked vehicles cruise control. In: Proceedings of 3rd international conference on internet of things and connected technologies (ICIoTCT)

5. Jain A, Roy BK (2019) Online control of a nonlinear autonomous vehicle in the presence of network delay. J Adv Res Dyn Control Syst (JARDCS)

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1. Dynamic Kalman filter-based velocity tracker for Intelligent vehicle;IECON 2021 – 47th Annual Conference of the IEEE Industrial Electronics Society;2021-10-13

2. Toward a collision avoidance system based on the integration of technologies;Proceedings of the 2021 ACM Southeast Conference;2021-04-15

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