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Merge pull request #24 from dasc-lab/feat/code
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2 parents 084b655 + 562def8 commit 538da1b

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---
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layout: code
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title: "Online Adaptive CBFs"
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date: 2024-10-22
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code: https://github.com/tkkim-robot/online_adaptive_cbf
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title: "Online Adaptive CBFs"
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date: 2024-10-22
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code: https://github.com/tkkim-robot/online_adaptive_cbf
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layout: code
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title: "Online Adaptive CBFs"
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date: 2024-10-22
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code: https://github.com/tkkim-robot/online_adaptive_cbf
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layout: code
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title: "Online Adaptive CBFs"
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date: 2024-10-22
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code: https://github.com/tkkim-robot/online_adaptive_cbf
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content/code/2024-safe-control.md

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layout: code
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title: "Safety-Critical Controllers for Robotic Navigation"
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date: 2024-07-10
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code: https://github.com/tkkim-robot/safe_control
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---

content/code/_index.md

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title: Code # force it to not be plural
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Here is some content

content/papers/2022-coverage-maximizing.md

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date: 2022-06-10
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image: /images/15astarPathOverCoverage.png
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venue: "IEEE ACC 2022"
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authors:
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authors:
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- kavinmgovindarajan
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- Ben Haydon
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- Kirti Mishra
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- Christopher Vermillion
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code: https://github.com/kmgovind/acc-2022
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code: https://github.com/kmgovind/acc-2022
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abstract: "The Gulf Stream, which comes within 100 km
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of the United States coastline in both the Florida Straits and
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the vicinity of Cape Hatteras, is estimated to possess over 160

content/papers/2022-differentially-flat.md

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# link to arxiv (optional)
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arxiv:
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# link to github (optional)
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code: https://github.com/dev10110/Multirate-Controllers-for-Differentially-Flat-Systems
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# link to video (optional)
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video:
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# link to pdf (optional)

content/papers/2022-observer-controller.md

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link: https://doi.org/10.1109/LCSYS.2022.3185142
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code: https://github.com/dev10110/robust-safe-observer-controllers
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abstract: "This letter addresses the synthesis of safety-critical controllers using estimate feedback. We propose an observer-controller interconnection to ensure that the nonlinear system remains safe despite bounded disturbances on the system dynamics and measurements that correspond to partial state information. The co-design of observers and controllers is critical, since even in undisturbed cases, observers and controllers designed independently may not render the system safe. We propose two approaches to synthesize observer-controller interconnections. The first approach utilizes Input-to-State Stable observers, and the second uses Bounded Error observers. Using these stability and boundedness properties of the observation error, we construct novel Control Barrier Functions that impose inequality constraints on the control inputs which, when satisfied, certifies safety. We propose quadratic program-based controllers to satisfy these constraints, and prove Lipschitz continuity of the derived controllers. Simulations and experiments on a quadrotor demonstrate the efficacy of the proposed methods."
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excerpt:
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pdf: /pdfs/2022-observer-controller.pdf

content/papers/2023-predictive-velocity.md

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date: 2023-07-03
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venue: "IEEE ACC 2023"
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authors:
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- kavinmgovindarajan
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- Ben Haydon
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- Christopher Vermillion

content/papers/eclares.md

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venue: "IEEE ICRA 2024"
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link: https://doi.org/10.1109/ICRA57147.2024.10611286
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arxiv: https://arxiv.org/abs/2310.06933
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code: https://github.com/kalebbennaveed/Eclares.git
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code: https://github.com/kalebbennaveed/Eclares
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video: https://youtu.be/1ZCgxlHitzk
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abstract: "Planning informative trajectories while considering the spatial distribution of the information over the environment, as well as constraints such as the robot’s limited battery capacity, makes the long-time horizon persistent coverage problem complex. Ergodic search methods consider the spatial distribution of environmental information while optimizing robot trajectories; however, current methods lack the ability to construct the target information spatial distribution for environments that vary stochastically across space and time. Moreover, current coverage methods dealing with battery capacity constraints either assume simple robot and battery models or are computationally expensive. To address these problems, we propose a framework called Eclares, in which our contribution is two-fold. 1) First, we propose a method to construct the target information spatial distribution for ergodic trajectory optimization using clarity, an information measure bounded between [0, 1]. The clarity dynamics allow us to capture information decay due to a lack of measurements and to quantify the maximum attainable information in stochastic spatiotemporal environments. 2) Second, instead of directly tracking the ergodic trajectory, we introduce the energy-aware (eware) filter, which iteratively validates the ergodic trajectory to ensure that the robot has enough energy to return to the charging station when needed. The proposed eware filter is applicable to nonlinear robot models and is computationally lightweight. We demonstrate the working of the framework through a simulation case study."
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pdf: /pdfs/2024-eclares.pdf

content/papers/iccbfs.md

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code: https://github.com/dev10110/Input-Constrained-Control-Barrier-Functions
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abstract: "This paper introduces the notion of an Input
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Constrained Control Barrier Function (ICCBF), as a method to
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synthesize safety-critical controllers for nonlinear control-affine

content/papers/sparsest_r_robust_graphs.md

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title: "Construction of the Sparsest Maximally r-Robust Graphs"
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# specify the date it was published
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date: 2024-03-01
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# 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.
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# 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.
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authors:
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- dimitrapanagou
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# give the main figure location, relative to /static/
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image: /images/n_r_robust_graphs.png
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# specify the conference or journal that it was published in
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venue: "IEEE CDC 2024"
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# link to publisher site (optional)
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link:
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arxiv: https://arxiv.org/abs/2409.19465
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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."
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content/papers/strong_r_icra.md

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title: "Maintaining Strong r-Robustness in Reconfigurable Multi-Robot Networks using Control Barrier Functions"
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# 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.
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# 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.
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- dimitrapanagou
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venue: Available on arXiv
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content/people/kavinmgovindarajan.md

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hugo.toml

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name = "Projects"
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[[menu.main]]
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name = "Code"
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url = "/code/"
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weight = 5
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layouts/code/list.html

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{{ define "main" }}
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<h1>{{ .Title }}</h1>
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<p class="d-none"> Rendered from layouts/code/list </p>
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<div class="row row-cols-auto">
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{{ range .Pages }}
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<div class="col py-3">
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<a href={{ .RelPermalink }}>
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{{ partial "github-repo-card" . }}
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</a>
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</div>
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layouts/code/single.html

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<div class="my-3">
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<h2>{{ .Title }}</h2>
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</div>
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{{ partial "github-repo-card" . }}
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{{ .Content }}
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{{ if .Params.bib }}
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<div class="card">
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layouts/papers/single.html

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{{ partial "github-repo-card" . }}
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layouts/partials/.style.html.swp

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{{/* Expects ".Params.code" to be of the format "https://github.com/username/repo" */}}
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{{/* Uses https://github.com/anuraghazra/github-readme-stats to render the card */}}
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{{/* split the string to get the username and repo string */}}
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{{ $github_split := split .Params.code "/" }}
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{{ $username := index $github_split 3 }}
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{{ $repo := index $github_split 4 }}
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<div class="repo">
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<a href={{ .Params.code }} target="_blank">
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<img
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>
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