대한임베디드공학회논문지 (IEMEK Journal of Embedded Systems and Applications)
- 제3권2호
- /
- Pages.102-108
- /
- 2008
- /
- 1975-5066(pISSN)
Map Building and Localization Based on Wave Algorithm and Kalman Filter
- Saitov, Dilshat (Dept. of Electrical Eng. Yeungnam Univ.) ;
- Choi, Jeong Won (School of Electronic Eng Kumoh National Institute of Technology) ;
- Park, Ju Hyun (Yeungnam univ.) ;
- Lee, Suk Gyu (Yeungnam univ.)
- 투고 : 2008.04.23
- 심사 : 2008.06.13
- 발행 : 2008.06.30
초록
This paper describes a mapping and localization based on wave algorithm[11] and Kalman filter for effective SLAM. Each robot in a multi robot system has its own task such as building a map for its local position. By combining their data into a shared map, the robot scans actively seek to verify their relative locations. For simultaneous localization the algorithm which is well known as Kalman Filter (KF) is used. For modelling the robot position we wish to know three parameters (x, y coordinates and its orientation) which can be combined into a vector called a state variable vector. The Kalman Filter is a smart way to integrate measurement data into an estimate by recognizing that measurements are noisy and that sometimes they should ignored or have only a small effect on the state estimate. In addition to an estimate of the state variable vector, the algorithm provides an estimate of the state variable vector uncertainty i.e. how confident the estimate is, given the value for the amount of error in it.