A Radar-Based Simultaneous Localization and Mapping Paradigm for Scattering Map Modeling
01 Aug 2018-
TL;DR: A Simultaneous Localization and Mapping paradigm with an adaptive genetic particle filter is migrated to the detection platform with microwave radar sensors and the simulation results indicate that the algorithm works accurately in terms of both map construction and platform positioning.
Abstract: In this paper, a Simultaneous Localization and Mapping (SLAM) paradigm with an adaptive genetic particle filter is migrated to the detection platform with microwave radar sensors. A closed-loop feedback scheme is implemented to obtain the position of radar platform as well as to construct a scattering map for surrounding object with either deterministic or stochastic echo-wave response. The simulation results indicate that the algorithm works accurately in terms of both map construction and platform positioning.
Citations
More filters
TL;DR: The problem of SLAM, its general model, framework, the difficulties, and leading approaches are described, and some of the most important approaches of all time are selected to understand the research development, current trends, and intellectual structure ofSLAM.
59 citations
01 Oct 2019
TL;DR: A simultaneous Localization and Mapping (SLAM) algorithm based on particle filter is implemented to construct occupancy grid maps and different feature extraction algorithms are applied in the architecture on maps constructed using measurement data with different degrees of sparsity.
Abstract: In this paper, a simultaneous Localization and Mapping (SLAM) algorithm based on particle filter is implemented to construct occupancy grid maps. A feature-extraction architecture consisting of two stages, i.e. map integration and high-level feature extraction, is proposed for the application in radar gird map matching for loop-closing purposes. Different feature extraction algorithms based are applied in the architecture on maps constructed using measurement data with different degrees of sparsity. The results are compared and discussed
Cites methods from "A Radar-Based Simultaneous Localiza..."
...SLAM based on the particle filter algorithm [5-6] is...
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01 Nov 2018
TL;DR: A Simultaneous Localization and Mapping algorithm for radar target detection is proposed to account for stochastic spread target as landmarks and a grid map construction method is developed for accurate reconstruction of the shape of spread targets.
Abstract: A Simultaneous Localization and Mapping (SLAM) algorithm for radar target detection is proposed to account for stochastic spread target as landmarks. A grid map construction method is developed for accurate reconstruction of the shape of spread targets. The simulation results indicate that the algorithm is able to deal with multiple stochastic landmarks within the proposed close-loop SLAM scheme.
Cites methods from "A Radar-Based Simultaneous Localiza..."
...After distinguishing the targets, if the target is deterministic, methodologies in [5-6] can be applied....
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References
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TL;DR: This paper describes the simultaneous localization and mapping (SLAM) problem and the essential methods for solving the SLAM problem and summarizes key implementations and demonstrations of the method.
Abstract: This paper describes the simultaneous localization and mapping (SLAM) problem and the essential methods for solving the SLAM problem and summarizes key implementations and demonstrations of the method. While there are still many practical issues to overcome, especially in more complex outdoor environments, the general SLAM method is now a well understood and established part of robotics. Another part of the tutorial summarized more recent works in addressing some of the remaining issues in SLAM, including computation, feature representation, and data association
3,760 citations
Additional excerpts
...The Simultaneous Localization and Mapping (SLAM), first introduced in the computer vision regime [1-3], generates and updates the map around a moving platform whilst simultaneously estimating the real-time position of the platform utilizing the map information....
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01 Jan 1996
TL;DR: The localization problem, the ability to accurately sense and estimate the location of a platform, lies at the heart of almost all AGV applications and is an essential precursor to more complex AGV tasks such as planing and task execution.
Abstract: This paper reviews and describes the state-of-the-art in localization of autonomous guided vehicles (AGVs). The localization problem, the ability to accurately sense and estimate the location of a platform, lies at the heart of almost all AGV applications. Solving the localization problem is an essential precursor to more complex AGV tasks such as planing and task execution.
71 citations
Additional excerpts
...The Simultaneous Localization and Mapping (SLAM), first introduced in the computer vision regime [1-3], generates and updates the map around a moving platform whilst simultaneously estimating the real-time position of the platform utilizing the map information....
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10 Apr 2016
TL;DR: In this article, a particle filter (PF) algorithm was proposed to solve the simultaneous localization and mapping (SLAM) problem of mobile robot with particle filter algorithm in non-linear non-Gaussian environments.
Abstract: In this paper, a novel methodology is proposed to solve the simultaneous localization and mapping (SLAM) problem of mobile robot with particle filter (PF) algorithm. Compared with Kalman filter (KF) and extended Kalman filter (EKF), PF has a better performance in non-linear non-Gaussian environments. A close-loop updating scheme is developed in which positions of the robot and landmarks are updated with particle filtering and a weighted averaging algorithm respectively, and are linked through an additional feedback and correction process. An adaptive re-sampling method is used to reduce the computational load. The results of the simulation indicate that the PF-SLAM algorithm can localize the robot and landmarks accurately, and the error of landmarks' estimation converges better than general SLAM algorithms.
8 citations
"A Radar-Based Simultaneous Localiza..." refers methods in this paper
...At each time step for the radar platform jth evaluation, this parameter set is evaluated and updated, and used for platform position update using the method in [4]....
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...Moreover, geometries formulated from deterministic scatterers are utilized for the close-loop correction of platform locations [4]....
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...Also, to improve the accuracy of the landmark positioning and platform location, an improved close-loop PFSLAM is proposed, by using the position of landmarks to further correct the platform location in the SLAM process [4]....
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