Merge pull request #36 from dasc-lab/test_joon

Revised Joon's ICRA paper info

Author: joonlee16

content/papers/2024/2024-sparsest_r_robust_graphs.md

@@ -13,15 +13,15 @@ image: /images/n_r_robust_graphs.png
 # specify the conference or journal that it was published in
 venue: "IEEE CDC 2024"
 # link to publisher site (optional)
-link:
+link: https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10886656
 # link to arxiv (optional)
 arxiv: https://arxiv.org/abs/2409.19465
 # link to github (optional)
 code:
 # link to video (optional)
 video:
 # link to pdf (optional)
-pdf:
+pdf: https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10886656
 # abstract
 abstract: "In recent years, the notion of r-robustness for the communication graph of the network has been introduced to address the challenge of achieving consensus in the presence of misbehaving agents. Higher r-robustness typically implies higher tolerance to malicious information towards achieving resilient consensus, but it also implies more edges for the communication graph. This in turn conflicts with the need to minimize communication due to limited resources in real-world applications (e.g., multi-robot networks). In this paper, our contributions are twofold. (a) We provide the subgraph structures and tight lower bounds on the number of edges required for graphs with a given number of nodes to reach the maximum robustness. (b) We then use the results of (a) to introduce two classes of graphs that utilize the least number of edges to maintain maximum robustness. Our work is validated through a series of simulations."
 # bib entry (optional). the |- is used to allow for multiline entry.

content/papers/2024/2024-strong_r_icra.md

@@ -0,0 +1,29 @@
+---
+layout: papers
+# specify the title of the paper
+title:  "Maintaining Strong r-Robustness in Reconfigurable Multi-Robot Networks using Control Barrier Functions"
+# specify the date it was published
+date: 2025-05-19
+# list the authors. if a "/people/id" page exists for the person, it will be linked. If not, the author's name is printed exactly as you typed it.
+authors:
+    - haejoonl
+    - dimitrapanagou
+# give the main figure location, relative to /static/
+image: /images/2025-icra_r.jpg
+# specify the conference or journal that it was published in
+venue: "IEEE ICRA 2025"
+# link to publisher site (optional)
+link: 
+# link to arxiv (optional)
+arxiv: https://arxiv.org/abs/2409.14675
+# link to github (optional)
+code: https://github.com/joonlee16/Resilient-Leader-Follower-CBF-QP
+# link to video (optional)
+video: https://www.youtube.com/watch?v=QhoByZszucg&feature=youtu.be
+# link to pdf (optional)
+pdf: https://arxiv.org/pdf/2409.14675
+# abstract
+abstract: "In leader-follower consensus, strong r-robustness of the communication graph provides a sufficient condition for followers to achieve consensus in the presence of misbehaving agents. Previous studies have assumed that robots can form and/or switch between predetermined network topologies with known robustness properties. However, robots with distance-based communication models may not be able to achieve these topologies while moving through spatially constrained environments, such as narrow corridors, to complete their objectives. This paper introduces a Control Barrier Function (CBF) that ensures robots maintain strong r-robustness of their communication graph above a certain threshold without maintaining any fixed topologies. Our CBF directly addresses robustness, allowing robots to have flexible reconfigurable network structure while navigating to achieve their objectives. The efficacy of our method is tested through various simulation and hardware experiments
+# bib entry (optional). the |- is used to allow for multiline entry."
+bib:
+---