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To Go or Not To Go? A Near Unsupervised Learning Approach For Robot
  Navigation

To Go or Not To Go? A Near Unsupervised Learning Approach For Robot Navigation

16 September 2017
Noriaki Hirose
Amir Sadeghian
P. Goebel
Silvio Savarese
    GAN
ArXivPDFHTML

Papers citing "To Go or Not To Go? A Near Unsupervised Learning Approach For Robot Navigation"

4 / 4 papers shown
Title
Learning Robotic Navigation from Experience: Principles, Methods, and
  Recent Results
Learning Robotic Navigation from Experience: Principles, Methods, and Recent Results
Sergey Levine
Dhruv Shah
SSL
49
21
0
13 Dec 2022
A Survey of Traversability Estimation for Mobile Robots
A Survey of Traversability Estimation for Mobile Robots
Christos Sevastopoulos
S. Konstantopoulos
46
34
0
22 Apr 2022
Entropic GANs meet VAEs: A Statistical Approach to Compute Sample
  Likelihoods in GANs
Entropic GANs meet VAEs: A Statistical Approach to Compute Sample Likelihoods in GANs
Yogesh Balaji
Hamed Hassani
Rama Chellappa
S. Feizi
GAN
DRL
41
20
0
09 Oct 2018
Path Planning in Support of Smart Mobility Applications using Generative
  Adversarial Networks
Path Planning in Support of Smart Mobility Applications using Generative Adversarial Networks
M. Mohammadi
Ala I. Al-Fuqaha
Jun-Seok Oh
GAN
15
23
0
23 Apr 2018
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