TY - JOUR ID - 71352 TI - A New Approach to Self-Localization for Mobile Robots Using Sensor Data Fusion JO - International Journal of Engineering JA - IJE LA - en SN - 1025-2495 AU - HoseinNezhad, Reza AU - Ashrafi, A. AU - Moshiri, B. AD - Engineering and IOndustrial Sciences, Swinburne University of Technology AD - , Sharif University of Technology AD - Electerical Engineering, University of Tehran Y1 - 2002 PY - 2002 VL - 15 IS - 2 SP - 145 EP - 156 KW - Sensor Data Fusion KW - Pose estimation KW - Dead Reckoning Calibration KW - Occupancy Grids KW - Maximum Likelihood KW - Map Building DO - N2 - This paper proposes a new approach for calibration of dead reckoning process. Using the well-known UMBmark (University of Michigan Benchmark) is not sufficient for a desirable calibration of dead reckoning. Besides, existing calibration methods usually require explicit measurement of actual motion of the robot. Some recent methods use the smart encoder trailer or long range finder sensors such as ultrasonic or laser range finders for automatic calibration. Manual measurement is necessary in the case of the robots that are not equipped with long-range detectors or such smart encoder trailer. Our proposed approach uses an environment map that is created by fusion of proximity data, in order to calibrate the odometry error automatically. In the new approach, the systematic part of the error is adaptively estimated and compensated by an efficient and incremental maximum likelihood algorithm. Actually, environment map data are fused with the odometry and current sensory data in order to acquire the maximum likelihood estimation. The advantages of the proposed approach are demonstrated in some experiments with Khepera robot. It is shown that the amount of pose estimation error is reduced by a percentage of more than 80%. UR - https://www.ije.ir/article_71352.html L1 - https://www.ije.ir/article_71352_bb1c034ab7bb52bfe820863df6ca503e.pdf ER -