SLAM으로 작성한 지도 품질의 상대적/정량적 비교를 위한 방법 제안
A New Method for Relative/Quantitative Comparison of Map Built by SLAM
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참고문헌
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초록
By a SLAM (simultaneous localization and mapping) method, we get a map of anenvironment for autonomous navigation of a robot. In this case, we want to know how accurate the mapis. Or we want to know which map is more accurate when different maps can be obtained by differentSLAM methods. So, several methods for map comparison have been studied, but they have their owndrawbacks. In this paper, we propose a new method which compares the accuracy or error of mapsrelatively and quantitatively. This method sets many corresponding points on both reference map andSLAM map, and computes the translational and rotational values of all corresponding points using leastsquaressolution. Analyzing the standard deviations of all translational and rotational values, we canknow the error of two maps. This method can consider both local and global errors while other methodscan deal with one of them, and this is verified by a series of simulations and real world experiments.
Abstract
By a SLAM (simultaneous localization and mapping) method, we get a map of anenvironment for autonomous navigation of a robot. In this case, we want to know how accurate the mapis. Or we want to know which map is more accurate when different maps can be obtained by differentSLAM methods. So, several methods for map comparison have been studied, but they have their owndrawbacks. In this paper, we propose a new method which compares the accuracy or error of mapsrelatively and quantitatively. This method sets many corresponding points on both reference map andSLAM map, and computes the translational and rotational values of all corresponding points using leastsquaressolution. Analyzing the standard deviations of all translational and rotational values, we canknow the error of two maps. This method can consider both local and global errors while other methodscan deal with one of them, and this is verified by a series of simulations and real world experiments.
참고문헌 (14)
- 장국현, "직선기반 SLAM에서의 루프결합", 로봇학회 논문지, 7(2), pp.120~128 (2012), 한국로봇학회
- 남창주, "광범위 환경에서 EKF-SLAM의 일관성 향상을 위한 새로운 관찰모델", 로봇학회 논문지, 7(1), pp.29~34 (2012), 한국로봇학회
- M. Dissanayake, "A solution to the simultaneous localization and mapping (slam) problem", IEEE Transactions on Robotics and Automation, 17(3), pp.229~241 (2001)
- G. Grisetti, "Improving grid-based SLAM with Rao-Blackwellized particle filters by adaptive proposals and selective resampling", Proceedings of IEEE ICRA 2005, pp.2432~2437 (2005)
- F. Lu, "Globally consistent range scan alignment for environment mapping", Journal of Autonomous Robots, 4(4), pp.333~349 (1997)
- O. Wulf, "Benchmarking urban six-degree-of-freedom simultaneous localization and mapping", Journal of Field Robotics, 25(3), pp.148~163 (2008)
- R, Iyekkettem, "A comparison of SLAM implementations for indoor mobile robots", Proceedings of IEEE, 2007, 1479~1484
- R. Kummerle, "On measuring the accuracy of SLAM algorithms", Autonomous Robots, 27(4), pp.387~407 (2009)
- B. Balaguer, "Toward quantitative comparisons of robot algorithms:Experiences with SLAM in simulation and real world systems", IROS 2007 workshop (2007)
- F. Amigoni, "Good experimental methodologies for robotic mapping: A proposal", Proceedings of IEEE ICRA 2007, pp.4176~4181 (2007)
- F. Lu, "Robot pose estimation in unknown environments by matching 2D range scans", Journal of Intelligent and Robotic Systems, 18(3), pp.249~275 (1997)
- K. Konolige, "A Low-Cost Laser Distance Sensor", Proceedings of IEEE ICRA 2008, pp.3002~3008 (2008)