Nonsmooth Barrier Functions With Applications to Multi-Robot Systems
By Paul Glotfelter, Jorge Cortés, Magnus Egerstedt. IEEE Control Systems Letters, 2017
357 citations recorded by the source corpus.
Subfields: Computational Theory and Mathematics, Computer Networks and Communications, Computer Vision and Pattern Recognition
View Paper: https://www.semanticscholar.org/paper/132d5e781bc30b1b7a0eae6084495f214f629613
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computational Theory and Mathematics
- Dimos V. Dimarogonas
- Calin A. Belta
- Wei Xiao
- Lars Lindemann
- Aaron D. Ames
- Magnus Egerstedt
- Samuel D. Coogan
- Koushil Sreenath
In Computer Networks and Communications
- Calin A. Belta
- Wei Xiao
- Dimos V. Dimarogonas
- Lars Lindemann
- Magnus Egerstedt
- Paulo Tabuada
- Aaron D. Ames
- Wei Ren
In Computer Vision and Pattern Recognition
- Calin A. Belta
- Wei Xiao
- Dimos V. Dimarogonas
- Lars Lindemann
- Magnus Egerstedt
- Koushil Sreenath
- Aaron D. Ames
- Veysel Gazi
Citations in the corpus
- Control Barrier Functions for Systems with High Relative Degree (2019, background): “Definition 3: (Control barrier function [8] [11]): Given a set C as in Eqn.”
- Control Barrier Functions: Theory and Applications (2019, background): “and enforcing differential constraints affine in the control variable ui, which are analogous to (7), as shown in [54].”
- Control Barrier Functions for Signal Temporal Logic Tasks (2019, methodology): “In order to use conjunctions as in the semantics in (2), while at the same time avoiding nonsmooth analysis as in [15], [16], a smooth under-approximation of the min-operator is used.”