Title
Ergodic Exploration Using Tensor Train: Applications in Insertion Tasks
Abstract
In robotics, ergodic control extends the tracking principle by specifying a probability distribution over an area to cover instead of a trajectory to track. The original problem is formulated as a spectral multiscale coverage problem, typically requiring the spatial distribution to be decomposed as Fourier series. This approach does not scale well to control problems requiring exploration in searc...
Year
DOI
Venue
2022
10.1109/TRO.2021.3087317
IEEE Transactions on Robotics
Keywords
DocType
Volume
Tensors,Task analysis,Trajectory,Measurement,End effectors,Dynamical systems,Robot sensing systems
Journal
38
Issue
ISSN
Citations 
2
1552-3098
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Suhan Shetty100.68
João Silvério2345.52
Sylvain Calinon31897117.63