Merge pull request #3 from dasc-lab/dev/add_papers

added devs papers

Author: dev10110

content/papers/2022-differentially-flat.md

@@ -0,0 +1,50 @@
+---
+layout: papers
+title:  "A Constructive Method for Designing Safe Multirate Controllers for Differentially-Flat Systems"
+date:  2021-12-17
+image: /images/2021-differentially-flat.png
+venue: "IEEE L-CSS and ACC 2022"
+authors:
+    - devanshagrawal
+    - Hardik Parwana
+    - Ryan K Cosner
+    - Ugo Rosolia
+    - Aaron D Ames
+    - dimitrapanagou 
+# give the main figure location, relative to /static/
+# link to publisher site (optional)
+link: https://doi.org/10.1109/LCSYS.2021.3136465
+# link to arxiv (optional)
+arxiv: 
+# link to github (optional)
+code: 
+# link to video (optional)
+video: 
+# link to pdf (optional)
+pdf: /pdfs/2021-differentially-flat.pdf
+# abstract
+abstract: "This paper introduces the notion of an Input
+Constrained Control Barrier Function (ICCBF), as a method to
+synthesize safety-critical controllers for nonlinear control-affine
+systems with input constraints. The method identifies a subset
+of the safe set of states, and constructs a controller to render the
+subset forward invariant. The feedback controller is represented
+as the solution to a quadratic program, which can be solved
+efficiently for real-time implementation. Furthermore, we show
+that ICCBFs are a generalization of Higher Order Control
+Barrier Functions, and thus are applicable to systems of non-
+uniform relative degree. Simulation results are presented for the
+adaptive cruise control problem, and a spacecraft rendezvous
+problem."
+bib: |-
+  @ARTICLE{9655322,
+    author={Agrawal, Devansh R. and Parwana, Hardik and Cosner, Ryan K. and Rosolia, Ugo and Ames, Aaron D. and Panagou, Dimitra},
+    journal={IEEE Control Systems Letters}, 
+    title={A Constructive Method for Designing Safe Multirate Controllers for Differentially-Flat Systems}, 
+    year={2022},
+    volume={6},
+    number={},
+    pages={2138-2143},
+    doi={10.1109/LCSYS.2021.3136465}
+  }
+---

content/papers/2022-observer-controller.md

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+---
+layout: papers
+title:  "Safe and robust observer-controller synthesis using control barrier functions"
+date:   2022-06-22
+image: /images/2022-observer-controller.png
+venue: "IEEE L-CSS and CDC 2022"
+authors: 
+    - devanshagrawal
+    - dimitrapanagou
+link: https://doi.org/10.1109/LCSYS.2022.3185142
+arxiv: 
+code: 
+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."
+excerpt: 
+pdf: /pdfs/2022-observer-controller.pdf
+bib: |-
+  @article{agrawal2022safe,
+    title={Safe and robust observer-controller synthesis using control barrier functions},
+    author={Agrawal, Devansh R and Panagou, Dimitra},
+    journal={IEEE Control Systems Letters},
+    volume={7},
+    pages={127--132},
+    year={2022},
+    publisher={IEEE}
+  }
+---

content/papers/2023-gatekeeper-iros.md

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+---
+layout: papers
+title:  "gatekeeper: Online safety verification and control for nonlinear systems in dynamic environments"
+date:   2023-10-01
+image: /images/2023-gatekeeper-iros.png
+venue: "IEEE IROS 2023"
+authors: 
+    - devanshagrawal
+    - Ruichang Chen
+    - dimitrapanagou
+link: https://doi.org/10.1109/IROS55552.2023.10341790 
+arxiv: https://arxiv.org/abs/2211.14361
+code: https://github.com/dev10110/gatekeeper 
+abstract: "This paper presents the gatekeeper algorithm, a real-time and computationally-lightweight method to ensure that nonlinear systems can operate safely in dynamic environments despite limited perception. gatekeeper integrates with existing path planners and feedback controllers by introducing an additional verification step that ensures that proposed trajectories can be executed safely, despite nonlinear dynamics subject to bounded disturbances, input constraints and partial knowledge of the environment. Our key contribution is that (A) we propose an algorithm to recursively construct committed trajectories, and (B) we prove that tracking the committed trajectory ensures the system is safe for all time into the future. The method is demonstrated on a complicated firefighting mission in a dynamic environment, and compares against the state-of-the-art techniques for similar problems."
+pdf: /pdfs/2023-gatekeeper-iros.pdf
+bib: |-
+  @inproceedings{agrawal2023gatekeeper,
+    title={gatekeeper: Online safety verification and control for nonlinear systems in dynamic environments},
+    author={Agrawal, Devansh and Chen, Ruichang and Panagou, Dimitra},
+    booktitle={2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
+    pages={259--266},
+    year={2023},
+    organization={IEEE}
+  } 
+---

content/papers/2023-perceivability.md

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+---
+layout: papers
+title:  "Sensor-based Planning and Control for Robotic Systems: Introducing Clarity and Perceivability"
+date:   2023-06-21
+image: /images/2023-clarity-and-perceivability.png
+venue: "IEEE L-CSS and CDC 2023"
+authors: 
+    - devanshagrawal
+    - dimitrapanagou
+link: https://doi.org/10.1109/LCSYS.2023.3288493
+arxiv: 
+code: 
+abstract: "In this letter, we first introduce an information measure, termed clarity , motivated by information entropy, and show that it has intuitive properties relevant to dynamic coverage control and informative path planning. Clarity defines on a scale of [0,1] the quality of the information that we have about a variable of interest in an environment. Clarity lower bounds the expected estimation error of any estimator, and is used as the information metric in the notion of perceivability , which is defined later on and is the primary contribution of this letter. Perceivability captures whether a given robotic (or more generally, sensing and control) system has sufficient sensing and actuation capabilities to gather desired information about an environment. We show that perceivability relates to the reachability of an augmented system, which encompasses the robot dynamics and the clarity about the environment, and we derive the corresponding Hamilton-Jacobi-Bellman equations. Thus, we provide an algorithm to measure an environment’s perceivability, and obtain optimal controllers that maximize information gain. In simulations, we demonstrate how clarity is a useful concept for planning trajectories, how perceivability can be determined using reachability analysis, and how a Control Barrier Function controller can be used to design controllers to maintain a desired level of information."
+pdf: /pdfs/2023-clarity-and-perceivability.pdf
+bib: |-
+  @article{agrawal2023sensor,
+    title={Sensor-based planning and control for robotic systems: Introducing clarity and perceivability},
+    author={Agrawal, Devansh R and Panagou, Dimitra},
+    journal={IEEE Control Systems Letters},
+    year={2023},
+    publisher={IEEE}
+  }
+---

content/papers/2024-advances-in-cbfs.md

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+---
+layout: papers
+title:  "Advances in the Theory of Control Barrier Functions: Addressing practical challenges in safe control synthesis for autonomous and robotic systems"
+date:   2024-03-12
+image: /images/2024-advances-in-cbfs.png
+venue: "Annual Reviews in Control 2024"
+authors: 
+    - Kunal Garg
+    - James Usevitch
+    - Joseph Breeden
+    - Mitchell Black
+    - devanshagrawal
+    - Hardik Parwana
+    - dimitrapanagou
+link: https://doi.org/10.1016/j.arcontrol.2024.100945
+arxiv: 
+code: 
+abstract: "This tutorial paper presents recent work of the authors that extends the theory of Control Barrier Functions (CBFs) to address practical challenges in the synthesis of safe controllers for autonomous systems and robots. We present novel CBFs and methods that handle safety constraints (i) with time and input constraints under disturbances, (ii) with high-relative degree under disturbances and input constraints, and (iii) that are affected by adversarial inputs and sampled-data effects. We then present novel CBFs and adaptation methods that prevent loss of validity of the CBF, as well as methods to tune the parameters of the CBF online to reduce conservatism in the system response. We also address the pointwise-only optimal character of CBF-induced control inputs by introducing a CBF formulation that accounts for future trajectories, as well as implementation challenges such as how to preserve safety when using output feedback control and zero-order-hold control. Finally we consider how to synthesize non-smooth CBFs when discontinuous inputs and multiple constraints are present."
+excerpt: 
+pdf: /pdfs/2024-advances-in-cbfs.pdf
+bib: |-
+  @article{garg2024advances,
+    title={Advances in the Theory of Control Barrier Functions: Addressing practical challenges in safe control synthesis for autonomous and robotic systems},
+    author={Garg, Kunal and Usevitch, James and Breeden, Joseph and Black, Mitchell and Agrawal, Devansh and Parwana, Hardik and Panagou, Dimitra},
+    journal={Annual Reviews in Control},
+    volume={57},
+    pages={100945},
+    year={2024},
+    publisher={Elsevier}
+  }
+---

content/papers/2024-multiagent-coverage.md

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+---
+layout: papers
+title:  "Multi-Agent Clarity-Aware Dynamic Coverage with Gaussian Processes"
+date: 2024-12-16
+image: /images/2024-multiagent-coverage.png
+venue: "IEEE CDC 2024"
+authors: 
+    - devanshagrawal
+    - dimitrapanagou
+arxiv:  https://arxiv.org/abs/2403.17917v1
+code: https://github.com/dev10110/multiagent-clarity-based-dynamic-coverage/ 
+abstract: "This paper presents two algorithms for multi-agent dynamic coverage in spatiotemporal environments, where
+the coverage algorithms are informed by the method of data
+assimilation. In particular, we show that by considering the
+information assimilation algorithm, here a Numerical Gaussian
+Process Kalman Filter, the influence of measurements taken
+at one position on the uncertainty of the estimate at another
+location can be computed. We use this relationship to propose
+new coverage algorithms. Furthermore, we show that the con-
+trollers naturally extend to the multi-agent context, allowing for
+a distributed-control central-information paradigm for multi-
+agent coverage. Finally, we demonstrate the algorithms through
+a realistic simulation of a team of UAVs collecting wind data
+over a region in Austria."
+pdf: /pdfs/2024-multiagent-coverage.pdf
+---

hugo.toml

@@ -1,6 +1,7 @@
 baseURL = 'https://dasc-lab.github.io/'
 languageCode = 'en-us'
 title = 'DASC Lab UMich'
+buildFuture = true
 
 [permalinks]
   blog = "/:filename/"

layouts/papers/list.html

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+  <div class="mt-3">
+    <h3> {{ .Key }} </h3>
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+      {{ partial "paper-card" . }} 
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