Self-supervised calibration for robotic systems

By Jérôme Maye, Paul Timothy Furgale, Roland Yves Siegwart. 2013

145 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Mechanical Engineering, Media Technology

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. Daniel Cremers
2. Davide Scaramuzza
3. Jakob J. Engel
4. David Caruso
5. Dinesh Thakur
6. Kostas Daniilidis
7. Tolga Özaslan
8. Alex Zihao Zhu

In Mechanical Engineering

1. David Caruso
2. Daniel Cremers
3. Jakob J. Engel
4. Vijay R. Kumar
5. Lerrel Pinto
6. Abhinav Kumar Gupta

In Media Technology

1. Dinesh Thakur
2. David Caruso
3. Daniel Cremers
4. Kostas Daniilidis
5. Tolga Özaslan
6. Alex Zihao Zhu
7. Jakob J. Engel
8. Vijay R. Kumar

Citations in the corpus

• Large-scale direct SLAM for omnidirectional cameras (2015, methodology): “The ξ parameter for this system has been estimated to 2.06 by offline calibration, using the Kalibr toolbox [23].”
• The Multivehicle Stereo Event Camera Dataset: An Event Camera Dataset for 3D Perception (2018, methodology): “The camera intrinsics, stereo extrinsics, and camera-IMU extrinsics are calibrated using the Kalibr toolbox3 [30], [31], [32], the extrinsics between the left DAVIS camera and Velodyne”