Globally consistent 3D mapping with scan matching

By Dorit Borrmann, Jan Elseberg, Kai Lingemann, Andreas Nüchter, Joachim Hertzberg. Robotics Auton. Syst., 2008

319 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition, Geology

View Paper: https://www.semanticscholar.org/paper/bb65cdec0fd9b6e98238e856894301cecb4b9a0b

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

1. Youfu Li
2. Shengyong Chen
3. Avideh Zakhor
4. Nicholas Corso
5. N. Kwok
6. John Kua
7. Sergey Levine
8. Fereshteh Sadeghi

In Computer Vision and Pattern Recognition

1. Youfu Li
2. Shengyong Chen
3. Avideh Zakhor
4. Nicholas Corso
5. N. Kwok
6. John Kua
7. Deng-Ping Fan

In Geology

1. Youfu Li
2. Sergey Levine
3. Fereshteh Sadeghi

Citations in the corpus

• On behalf of: Multimedia Archives (2012, unknown): “Later work, such as that of Borrmann et al. (2008), extends this approach to 3D and sparse constraint matrices, which speeds up the method.”
• Active vision in robotic systems: A survey of recent developments (2011, background): “More details of this topic are related to the research on simultaneous localization and mapping (SLAM) which is also a challenging problem and has been widely investigated (Gonzalez-Banos and Latombe 2002; Borrmann et al. 2008; Frintrop and Jensfelt 2008a; Nuchter and Hertzberg 2008).”
• Automatic loop closure detection using multiple cameras for 3D indoor localization (2012, background): “Given the input laser scans and OS data at t1 and t2, the 2×ICP+OS algorithm provides an estimate of the linear 6 DOF transformation from the pose at t1 to the pose at t2 by running ICP twice, once on the yaw scanner and once on the pitch scanner.”