On navigation of a robotic land vehicle

Bernard Friedland; Hong Ding

doi:10.2514/6.1993-3822

On navigation of a robotic land vehicle

Bernard Friedland, Hong Ding

Electrical and Computer Engineering

Research output: Contribution to conference › Paper › peer-review

Abstract

Estimation of the state of a robotic vehicle with independently-driven wheels is considered. The sensors in this application measure wheel rotation, angular velocity, and range from a fixed station. In addition to use of an extended Kalman filter for fusion of the data from these sensors, a simplified technique to reduced computational requirements is presented. Using dynamic parameters of an existing experimental vehicle, performance of the filters was simulated and compared. It was found that the simplified technique rivals the extended Kalman filter in performance but has a significant computational advantage.

Original language	English (US)
Pages	1083-1087
Number of pages	5
DOIs	https://doi.org/10.2514/6.1993-3822
State	Published - 1993
Event	Guidance, Navigation and Control Conference, 1993 - Monterey, United States Duration: Aug 9 1993 → Aug 11 1993

Other

Other	Guidance, Navigation and Control Conference, 1993
Country/Territory	United States
City	Monterey
Period	8/9/93 → 8/11/93

All Science Journal Classification (ASJC) codes

Aerospace Engineering
Control and Systems Engineering

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10.2514/6.1993-3822

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title = "On navigation of a robotic land vehicle",

abstract = "Estimation of the state of a robotic vehicle with independently-driven wheels is considered. The sensors in this application measure wheel rotation, angular velocity, and range from a fixed station. In addition to use of an extended Kalman filter for fusion of the data from these sensors, a simplified technique to reduced computational requirements is presented. Using dynamic parameters of an existing experimental vehicle, performance of the filters was simulated and compared. It was found that the simplified technique rivals the extended Kalman filter in performance but has a significant computational advantage.",

author = "Bernard Friedland and Hong Ding",

note = "Publisher Copyright: {\textcopyright} 1993 by Bernard Friedland.; Guidance, Navigation and Control Conference, 1993 ; Conference date: 09-08-1993 Through 11-08-1993",

year = "1993",

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language = "English (US)",

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AU - Friedland, Bernard

AU - Ding, Hong

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N2 - Estimation of the state of a robotic vehicle with independently-driven wheels is considered. The sensors in this application measure wheel rotation, angular velocity, and range from a fixed station. In addition to use of an extended Kalman filter for fusion of the data from these sensors, a simplified technique to reduced computational requirements is presented. Using dynamic parameters of an existing experimental vehicle, performance of the filters was simulated and compared. It was found that the simplified technique rivals the extended Kalman filter in performance but has a significant computational advantage.

AB - Estimation of the state of a robotic vehicle with independently-driven wheels is considered. The sensors in this application measure wheel rotation, angular velocity, and range from a fixed station. In addition to use of an extended Kalman filter for fusion of the data from these sensors, a simplified technique to reduced computational requirements is presented. Using dynamic parameters of an existing experimental vehicle, performance of the filters was simulated and compared. It was found that the simplified technique rivals the extended Kalman filter in performance but has a significant computational advantage.

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T2 - Guidance, Navigation and Control Conference, 1993

Y2 - 9 August 1993 through 11 August 1993

ER -

On navigation of a robotic land vehicle

Abstract

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All Science Journal Classification (ASJC) codes

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