The Office Marathon: Robust navigation in an indoor office environment

By Eitan Marder-Eppstein, Eric Berger, Tully Foote, Brian P. Gerkey, Kurt Konolige. IEEE International Conference on Robotics and Automation, 2010

580 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Networks and Communications, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/b259ddda2aab356f323460d30d441f49a23eb17c

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Citations in the corpus

Autonomous door opening and plugging in with a personal robot (2010, methodology): “…described in the previous section, we rely on two key pieces of supporting infrastructure: navigation and executive control. a) Navigation: The PR2 autonomously navigates in an indoor office environment using a 2D occupancy grid map built from base laser scans, with 2.5 cm grid resolution [20].”
Lessons from the Amazon Picking Challenge: Four Aspects of Building Robotic Systems (2016, methodology): “the Amazon Picking Challenge used ROS [40] and relied on various standard modules, for example, for visual processing [7, 43] and navigation [32].”
A Fully-Autonomous Aerial Robot for Search and Rescue Applications in Indoor Environments using Learning-Based Techniques (2018, methodology): “A detailed explanation of the algorithm and its components can be reviewed at [33].”
RTAB‐Map as an open‐source lidar and visual simultaneous localization and mapping library for large‐scale and long‐term online operation (2018, methodology): “These live comparisons can then help to reveal flaws and limitations inherent to the sensor chosen when combined with standard navigation approaches like ROS’ navigation stack [Marder-Eppstein et al., 2010].”
Robot navigation in dense human crowds: Statistical models and experimental studies of human–robot cooperation (2015, background): “[31], Foka and Trahanias [34], Bauer et al.”
Robot Operating System 2: Design, architecture, and uses in the wild (2022, background): “Its commercial rise was the result of flagship projects providing autonomous navigation, simulation, visualization, control, and more [2], [3], [4].”
Learning Navigation Behaviors End-to-End With AutoRL (2018, background): “This “stacked” approach has demonstrated reliable operation over long distances [26].”
Fetch & Freight : Standard Platforms for Service Robot Applications (2016, background): “Significant research has been done on PR2 robots, and there are numerous published results [3], [4], [5], many of which can be reproduced in labs around the”
The Marathon 2: A Navigation System (2020, methodology): “posed in 2010, it provided a rich and configurable navigation system that has been reconfigured for use on a variety of robot platforms [1].”