Title :
Mobile Robot Localisation for Indoor Environments Based on Ceiling Pattern Recognition
Author :
Dias, Francisco ; Schafer, Hanna ; Natal, Leonardo ; Cardeira, Carlos
Author_Institution :
Inst. Super. Tecnico, Univ. de Lisboa, Lisbon, Portugal
Abstract :
In this paper a multi-modal localisation system, that estimates a robot position in indoor environments using only on-board sensors, namely a webcam and a compass, is presented. Ceiling lights are used as beacons. Their position is previously known or self-learned during normal operation. Markov Localisation (ML) is both simulated and experimentally validated. For the prediction step it combines IMU (Inertial Measurement Unit) data and image parameters to compute the attitude of the robot. The update step is then calculated by measuring the distance to possibly visible ceiling lights. The experimental validation of the proposed solution shows that the robot position estimate converges to its real position and the error is kept within decimetres of magnitude.
Keywords :
Markov processes; mobile robots; pattern recognition; position control; IMU data; ML; Markov localisation; ceiling lights; ceiling pattern recognition; compass; image parameters; indoor environment; inertial measurement unit; mobile robot localisation; on-board sensors; robot position estimation; webcam; Convergence; Mobile robots; Robot kinematics; Robot sensing systems; Trajectory; Computer vision; Mobile robots; Robot sensing systems;
Conference_Titel :
Autonomous Robot Systems and Competitions (ICARSC), 2015 IEEE International Conference on
Conference_Location :
Vila Real
DOI :
10.1109/ICARSC.2015.32