A bearing-only 2D/3D-homing method under a visual servoing framework
By Ming Liu, Cédric Pradalier, Qijun Chen, Roland Yves Siegwart. 2010
41 citations recorded by the source corpus.
Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition
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
- Lei Tai
- Ming Liu
- Roland Yves Siegwart
- Davide Scaramuzza
- Wolfram Burgard
- Guoquan Huang
- Daniel Cremers
- Markus Achtelik
In Computer Vision and Pattern Recognition
- Lei Tai
- Ming Liu
- Roland Yves Siegwart
- Cédric Pradalier
- Davide Scaramuzza
- Wolfram Burgard
- Guoquan Huang
- Daniel Cremers
Citations in the corpus
- A Survey of Deep Network Solutions for Learning Control in Robotics: From Reinforcement to Imitation (2016, neutral): “ed for the homing vector prediction in the mobile robot visual homing problem. As a basic and low-cost navigation ability, traditionally the homing vector was motivated by visual servoing algorithms (Liu et al., 2010, 2012, 2013b). The result (Tai and Liu, 2016b) showed that when the same target as ”
- Visual Homing From Scale With an Uncalibrated Omnidirectional Camera (2013, methodology): “In our previous work [12], we gave a proof of the convergence of a simplified bearing-only method, based on the Lyapunov stability theory.”
- Deep-learning in Mobile Robotics - from Perception to Control Systems: A Survey on Why and Why not (2016, background): “As a basic and low-cost navigation ability, traditionally the homing vector was motivated by visual servoing algorithms (Liu et al., 2010, 2012, 2013).”