Localization and tracking of indoor mobile robot with beacons and dead reckoning sensors

Author

Lobo, Allan ; Kadam, Ronit ; Shajahan, Shabeeha ; Malegam, Keshad ; Wagle, Kranti ; Surve, Sunil

Author_Institution

Fr. Conceicao Rodrigues Coll. of Eng., Mumbai, India

fYear

2014

fDate

1-2 March 2014

Firstpage

1

Lastpage

4

Abstract

Autonomous robots must be able to localize themselves in an environment. We are interested in the real time pose estimation of a single surveillance robot based on the Odometry algorithm and Dead Reckoning using Inertial Measurement Unit (IMU) sensors. This approach is subjected to accumulated errors due to slippage and drift respectively. Algorithm proposed in this paper uses Trilateration with Extended Kalman filter. We found that our approach reduces the error.

Keywords

Global Positioning System; Kalman filters; distance measurement; image sensors; indoor environment; inertial systems; mobile robots; nonlinear filters; pose estimation; robot vision; surveillance; GPS; IMU sensors; autonomous robots; beacons; dead reckoning sensors; drift; extended Kalman filter; indoor mobile robot localization; indoor mobile robot tracking; inertial measurement unit sensors; odometry algorithm; real time pose estimation; single surveillance robot; slippage; trilateration; Equations; Kalman filters; Mathematical model; Mobile robots; Robot kinematics; Sensors; Dead Reckoning; Inertial Measurement Unit(IMU); Kalman filter; Localization; Odometry; Trilateration;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical, Electronics and Computer Science (SCEECS), 2014 IEEE Students' Conference on

Conference_Location

Bhopal

Print_ISBN

978-1-4799-2525-4

Type

conf

DOI

10.1109/SCEECS.2014.6804452

Filename

6804452