Abstract
This paper presents an integrated vision-based navigation system for small autonomous aircraft. Previously developed sensor fusion algorithms based on the Unscented Kalman Filter (UKF) are combined with an adaptive receding horizon controller (ARHC) for guidance. Control and planning horizons are computed based on the sensor range and the effective speed of the UAV, which is computed as a weighted sum of estimated vehicle speed and time rate of change of the uncertainty of the obstacle position estimates. Simulation results demonstrate the integrated system and illustrate the value of the adaptive approach.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings of the 2006 American Control Conference |
| Pages | 2160-2165 |
| Number of pages | 6 |
| Volume | 2006 |
| State | Published - 2006 |
| Event | 2006 American Control Conference - Minneapolis, MN, United States Duration: Jun 14 2006 → Jun 16 2006 |
Other
| Other | 2006 American Control Conference |
|---|---|
| Country | United States |
| City | Minneapolis, MN |
| Period | 6/14/06 → 6/16/06 |
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All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
Cite this
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Adaptive receding horizon control for vision-based navigation of small unmanned aircraft. / Frew, Eric W.; Langelaan, Jacob Willem; Sungmoon, Joo.
Proceedings of the 2006 American Control Conference. Vol. 2006 2006. p. 2160-2165 1656539.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Adaptive receding horizon control for vision-based navigation of small unmanned aircraft
AU - Frew, Eric W.
AU - Langelaan, Jacob Willem
AU - Sungmoon, Joo
PY - 2006
Y1 - 2006
N2 - This paper presents an integrated vision-based navigation system for small autonomous aircraft. Previously developed sensor fusion algorithms based on the Unscented Kalman Filter (UKF) are combined with an adaptive receding horizon controller (ARHC) for guidance. Control and planning horizons are computed based on the sensor range and the effective speed of the UAV, which is computed as a weighted sum of estimated vehicle speed and time rate of change of the uncertainty of the obstacle position estimates. Simulation results demonstrate the integrated system and illustrate the value of the adaptive approach.
AB - This paper presents an integrated vision-based navigation system for small autonomous aircraft. Previously developed sensor fusion algorithms based on the Unscented Kalman Filter (UKF) are combined with an adaptive receding horizon controller (ARHC) for guidance. Control and planning horizons are computed based on the sensor range and the effective speed of the UAV, which is computed as a weighted sum of estimated vehicle speed and time rate of change of the uncertainty of the obstacle position estimates. Simulation results demonstrate the integrated system and illustrate the value of the adaptive approach.
UR - http://www.scopus.com/inward/record.url?scp=34047198114&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=34047198114&partnerID=8YFLogxK
M3 - Conference contribution
SN - 1424402107
SN - 9781424402106
VL - 2006
SP - 2160
EP - 2165
BT - Proceedings of the 2006 American Control Conference
ER -