fix info

Author: tkkim-robot

content/news/2024-cdc.md

@@ -0,0 +1,7 @@
+---
+layout: news
+title:  "Four papers accepted at CDC 2024!"
+date:  2024-07-24
+---
+
+Four papers have been accepted at IEEE CDC 2024 (including one L-CSS paper)! Check out: ["Construction of the Sparsest Maximally r-Robust Graphs"](/papers/2024-sparsest_r_robust_graphs.md), ["Multi-Agent Clarity-Aware Dynamic Coverage with Gaussian Processes"](/papers/2024-multiagent-coverage.md), ["Safety-Aware Trajectory Tracking using High-Order Control Barrier Functions"](/papers/2024-safety-aware-tracking.md), and ["Robust Safety-Critical Control for Systems With Sporadic Measurements and Dwell-Time Constraints"](/papers/2024-breeden-robust_safety_critical_control_for_systems_with_sporadic_measurements_and_dwell_time_constraints.md).

content/papers/2024/2024-black-risk_aware_fixed_time_stabilization_of_stochastic_systems_under_measurement_uncertainty.md

@@ -35,6 +35,6 @@ key: conf/amcc/BlackFHP24
 layout: papers
 link: https://doi.org/10.23919/ACC60939.2024.10644792
 title: Risk-Aware Fixed-Time Stabilization of Stochastic Systems Under Measurement
-  Uncertainty.
-venue: ACC
+  Uncertainty
+venue: ACC 2024
 ---

content/papers/2024/2024-breeden-robust_safety_critical_control_for_systems_with_sporadic_measurements_and_dwell_time_constraints.md

@@ -27,6 +27,6 @@ key: journals/csysl/BreedenZP24
 layout: papers
 link: https://doi.org/10.1109/LCSYS.2024.3410631
 title: Robust Safety-Critical Control for Systems With Sporadic Measurements and Dwell-Time
-  Constraints.
-venue: IEEE Control. Syst. Lett.
+  Constraints
+venue: IEEE Control Systems Letteter 2024
 ---

content/papers/2024/2024-safety-aware-tracking.md

@@ -0,0 +1,31 @@
+---
+layout: papers
+# specify the title of the paper
+title:  "Safety-Aware Trajectory Tracking using High-Order Control Barrier Functions"
+# specify the date it was published
+date: 2024-03-01
+# 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:
+    - Panagiotis Rousseas
+    - dimitrapanagou
+    - Kostas Kyriakopoulos
+# give the main figure location, relative to /static/
+image: /images/2024-safety-aware-tracking.png
+# specify the conference or journal that it was published in
+venue: "IEEE CDC 2024"
+# link to publisher site (optional)
+link: 
+# link to arxiv (optional)
+arxiv: 
+paper: https://ieeexplore.ieee.org/abstract/document/10886244
+# link to github (optional)
+code:
+# link to video (optional)
+video:
+# link to pdf (optional)
+pdf: 
+# abstract
+abstract: "A novel method on safety-aware trajectory tracking is presented in this work. The proposed scheme employs Control Barrier Functions (CBFs) along with a latent-space representation over the barrier and its derivatives. While such representations have also been employed in the literature, the innovation of the proposed method lies in formulating a novel tracking problem on the latent space, enabling for the shape of linear class−K functions that are included in the safety condition induced by the control barrier function to be chosen constructively. Additionally, the aforementioned safety condition is modified based on the latent-space tracking through the addition of an extra term. This enables maintaining safety guarantees and is demonstrated to provide decreased tracking errors compared to the nominal control barrier function scheme. Numerical simulations validate the efficacy of the proposed scheme, as well as its ability for online implementation."
+# bib entry (optional). the |- is used to allow for multiline entry.
+bib:
+---

content/papers/2024/2024-tekriwal-formally_verified_asymptotic_consensus_in_robust_networks.md

@@ -26,5 +26,5 @@ key: conf/tacas/TekriwalTJKP24
 layout: papers
 link: https://doi.org/10.1007/978-3-031-57246-3_14
 title: Formally verified asymptotic consensus in robust networks.
-venue: TACAS (1)
+venue: Tools and Algorithms for the Construction and Analysis of Systems 2024
 ---

content/papers/2025-conformal-prediction.md

@@ -0,0 +1,32 @@
+---
+layout: papers
+# specify the title of the paper
+title:  "Conformal Prediction in the Loop: Risk-Aware Control Barrier Functions for Stochastic Systems with Data-Driven State Estimators"
+# specify the date it was published
+date: 2025-05-20
+# 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:
+    - junhuizhang
+    - Bardh Hoxha
+    - Georgios Fainekos
+    - dimitrapanagou
+# give the main figure location, relative to /static/
+image: /images/2025-conformal-prediction.png
+# specify the conference or journal that it was published in
+venue: "IEEE Control Systems Letters 2025"
+# link to project page (optional)
+projectpage:
+# link to publisher site (optional)
+link:
+# link to arxiv (optional)
+arxiv:
+# link to github (optional)
+paper: https://ieeexplore.ieee.org/abstract/document/11007767
+code:
+# link to video (optional)
+video:
+# link to pdf (optional)
+pdf:
+# abstract
+abstract: "This paper proposes a sampled-data, measurementrobust, risk-aware control barrier function (RA-CBF) framework for stochastic systems with measurement uncertainty. In this framework, what is available for control design are measurements of the system states, which are subject to unknown noise. First, in order to estimate the system states from these measurements, an offline-trained neural network is employed as a state estimator. Next, to quantify the performance of the state estimator, the state space is discretized, and calibration datasets are sampled from the grid points. Conformal prediction is then implemented, providing the estimation error bound with user-defined probability. In addition, we leverage the estimation error bound into sampleddata robust RA-CBF design, such that the probability that the state of the system enters the unsafe set during a finite time horizon is bounded by a desired threshold. Various case studies demonstrate the effectiveness of the proposed method."
+---

layouts/partials/paper-card.html

@@ -59,6 +59,9 @@
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           {{ end }}
+          {{ if .Params.paper }}
+          <a href="{{ .Params.paper}}" target="_blank">paper</a> /
+          {{ end }}
           {{ if .Params.arxiv }}
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