Terrain traversability analysis methods for unmanned ground vehicles: A survey
By Panagiotis Papadakis. Engineering applications of artificial intelligence, 2013
317 citations recorded by the source corpus.
Subfields: Aerospace Engineering, Biomedical Engineering, Computer Vision and Pattern Recognition
View Paper: https://www.semanticscholar.org/paper/819098482013b84043ff5d8b06a88608e4a5f527
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
- Noriaki Hirose
- Alfonso J. García-Cerezo
- Carlos Jesús Pérez-del-Pulgar
- J. Sánchez-Ibáñez
- Marynel Vázquez
- Patrick Goebel
- Amir Sadeghian
- Silvio Savarese
In Biomedical Engineering
In Computer Vision and Pattern Recognition
- Amir Sadeghian
- Silvio Savarese
- Noriaki Hirose
- Marynel Vázquez
- Patrick Goebel
- Alfonso J. García-Cerezo
- Carlos Jesús Pérez-del-Pulgar
- J. Sánchez-Ibáñez
Citations in the corpus
- Path Planning for Autonomous Mobile Robots: A Review (2021, methodology): “The magnitude of gravity can also affect the dynamics of the interaction between the robot and the terrain [30,69].”
- GONet: A Semi-Supervised Deep Learning Approach For Traversability Estimation (2018, background): “Common approaches to recognize non-traversable paths during robot navigation use bumpers or depth measurements [9].”
- Learning Ground Traversability From Simulations (2017, unknown): “prevailing) component of all related literature [3].”