Using laser range data for 3D SLAM in outdoor environments
By Dave Cole, Paul M. Newman. Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006., 2006
385 citations recorded by the source corpus.
Subfields: Aerospace Engineering, Environmental Engineering, Geology
View Paper: https://www.semanticscholar.org/paper/9f52e886f5f81dc0ccfb1ab596f1b6264e37096d
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Aerospace Engineering
- Cyrill Stachniss
- Andreas Nüchter
- Joachim Hertzberg
- Martin Magnusson
- Wolfram Burgard
- Olivier Aycard
- M. Bosse
- Asma Azim
In Environmental Engineering
- M. Bosse
- Robert Zlot
- Khalid Yousif
- Reza Hoseinnezhad
- Olivier Aycard
- Cyrill Stachniss
- Wolfram Burgard
- Asma Azim
In Geology
- Joachim Hertzberg
- Andreas Nüchter
- Khalid Yousif
- Reza Hoseinnezhad
- Olivier Aycard
- Cyrill Stachniss
- Wolfram Burgard
- Asma Azim
Citations in the corpus
- An Overview to Visual Odometry and Visual SLAM: Applications to Mobile Robotics (2015, background): “SLAM has been extensively studied in the past couple of decades [48,66,91] resulting in many different solutions using different sensors, including sonar sensors [71], IR sensors [1] and LASER scanners [26].”
- OctoMap : A Probabilistic , Flexible , and Compact 3 D Map Representation for Robotic Systems (2010, methodology): “Point clouds have been used in several 3D SLAM systems such as [2], [12].”
- Simultaneous Localization and Mapping: A Survey of Current Trends in Autonomous Driving (2017, neutral): “Another approach was proposed in [152] where errors are redistributed in a probabilistic fashion around the past trajectory when a loop is identified.”
- Detection, classification and tracking of moving objects in a 3D environment (2012, methodology): “is successfully used in [1] and [7] for 3D mapping of outdoor environment.”
- OctoMap: an efficient probabilistic 3D mapping framework based on octrees (2013, methodology): “This point cloud approach has been used in several 3D SLAM systems such as those presented by Cole and Newman (2006) as well as in the SLAM approach of Nüchter et al.”
- Globally consistent 3D mapping with scan matching (2008, background): “Weingarten et al. [37] and Cole et al. [8] use an extended Kalman filter on the mapping problem.”
- Continuous 3D scan-matching with a spinning 2D laser (2009, background): “It is also possible to fit the vehicle with a secondary sensor (such as an inertial measurement unit, GPS, or even another 2D laser) to help register each individual scan (e.g., [8], [9], [10]); however, errors from these devices must still be corrected in order to generate a consistent map.”