Improving Grid-based SLAM with Rao-Blackwellized Particle Filters by Adaptive Proposals and Selective Resampling

By Giorgio Grisetti, Cyrill Stachniss, Wolfram Burgard. Proceedings of the 2005 IEEE International Conference on Robotics and Automation, 2005

869 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Electrical and Electronic Engineering, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/adbf573fff1a63ce417561ec12fa404b6d3fc687

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Citations in the corpus

On behalf of: Multimedia Archives (2012, neutral): “…20 (Fairfield et al., 2006; Tomono, 2007), 30–40 (Stachniss et al., 2005), 20–160 (Welle et al., 2010), 50 (Kuemmerle et al., 2009), up to 100 (Grisetti et al., 2005), 100–200 (Marks et al., 2009), 200 (Schroeter and Gross, 2008), 250 (Koenig et al., 2008), 400 (Barkby et al., 2009), and…”
Deep Local Trajectory Replanning and Control for Robot Navigation (2019, methodology): “JackRabbot’s software stack uses the Robot Operating System (ROS) [62] for inter-process communication and logging, OpenSlam’s Gmapping for creating environment maps [63], ROS’s Adaptive Monte Carlo Localization algorithm for pose estimation [64], and YOLO [65] and DeepSort [66] for visually detecti”
Multi-robot Simultaneous Localization and Mapping using Particle Filters (2005, background): “In order to make this approach manageable, one requires either very good action models (Hähnel et al. 2003) or very good proposal distributions (Grisetti et al. 2005).”
Information Gain-based Exploration Using Rao-Blackwellized Particle Filters (2005, background): “As can be seen from this experiment, as soon as the robot gets too uncertain about its pose, it performs place re-visiting actions or chooses exploration actions which also reduce its pose uncertainty due to the information gathered along the path.”
An Overview to Visual Odometry and Visual SLAM: Applications to Mobile Robotics (2015, neutral): “c Occupancy grid map [51]”
A Review of Visual-LiDAR Fusion based Simultaneous Localization and Mapping (2020, methodology): “For laser scans, geometric descriptors are used like lines, planes, or spheres.”
A Review of Point Cloud Registration Algorithms for Mobile Robotics (2015, methodology): “Multiple initial guesses from the same external motion model and based on particle filters are also used in robotics [Grisetti et al., 2005] and in human body motion tracking [Kim, 2010].”
Simultaneous localization and mapping (SLAM): part II (2006, methodology): “Several recent FastSLAM hybrids use pose-aligned scans or grids in place of a landmark map [14], [20], [24].”
Real-time loop closure in 2D LIDAR SLAM (2016, background): “Two common approaches for addressing the remaining local error accumulation are particle filter and graph-based SLAM [2], [8].”
Autonomous multi-floor indoor navigation with a computationally constrained MAV (2011, methodology): “Both particle filter-based occupancy grid [10] and feature-based [11, 12] methods perform well in practice.”