Recursive scan-matching SLAM
نویسندگان
چکیده
This paper presents Scan-SLAM, a new generalization of simultaneous localization and mapping (SLAM). SLAM implementations based on extended Kalman filter (EKF) data fusion have traditionally relied on simple geometric models for defining landmarks. This limits EKF-SLAM to environments suited to such models and tends to discard much potentially useful data. The approach presented in this paper is a marriage of EKF-SLAM and scan correlation. Landmarks are no longer defined by analytical models; instead they are defined by templates composed of raw sensed data. These templates can be augmented as more data become available so that the landmark definition improves with time. A new generic observation model is derived that is generated by scan correlation, and this permits stochastic location estimation for landmarks with arbitrary shape within the Kalman filter framework. The statistical advantages of an EKF representation are augmented with the general applicability of scan matching. Scan matching also serves to enhance data association reliability by providing a shape metric for landmark disambiguation. Experimental results in an outdoor environment are presented which validate the algorithm. c © 2006 Elsevier B.V. All rights reserved.
منابع مشابه
Scan-SLAM: Recursive Mapping and Localisation with Arbitrary-Shaped Landmarks
Scan-SLAM is a simultaneous localisation and mapping algorithm that combines scan-matching methods with recursive estimation of landmark locations (using an EKF or other Bayesian filter). The scan-matching capability allows landmarks with arbitrary shapes to be modelled directly by sensed data and tracked within a conventional filter framework. This paper presents the essential Scan-SLAM algori...
متن کاملMultiple Laser Polar Scan Matching with Application to SLAM
Polar Scan Matching is one of the methods of point to point scan matching for Simultaneous Localization and Mapping Application. It works in the original laser polar coordinate system and therefore eliminates the need for an expensive correspondence search as in other scan matching methods by using the matching bearing association rule. However, most of the low-cost laser range finders availabl...
متن کاملScan-SLAM: Combining EKF-SLAM and Scan Correlation
This paper presents a new generalisation of simultaneous localisation and mapping (SLAM). SLAM implementations based on extended Kalman filter (EKF) data fusion have traditionally relied on simple geometric models for defining landmarks. This limits EKF-SLAM to environments suited to such models and tends to discard much potentially useful data. The approach presented in this paper is a marriag...
متن کاملA Fast and Robust Feature-Based Scan-Matching Method in 3D SLAM and the Effect of Sampling Strategies
Simultaneous localization and mapping (SLAM) plays an important role in fully autonomous systems when a GNSS (global navigation satellite system) is not available. Studies in both 2D indoor and 3D outdoor SLAM are based on the appearance of environments and utilize scan-matching methods to find rigid body transformation parameters between two consecutive scans. In this study, a fast and robust ...
متن کاملScan Matching for Graph SLAM in Indoor Dynamic Scenarios
SLAM (Simultaneous Localization And Mapping) plays an essential and important role for mobile robotic autonomous navigation. SLAM in dynamic environments with moving objects is a challenging problem. We focus on scan matching for Graph-SLAM in indoor dynamic scenarios. Scan matching algorithm is proposed and implemented, which consists of the following phases: first, conditioned Hough Transform...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Robotics and Autonomous Systems
دوره 55 شماره
صفحات -
تاریخ انتشار 2007