Charles Dawson

Orcid: 0000-0002-8371-5313

Affiliations:

Massachusetts Institute of Technology, Cambridge, MA, USA

According to our database¹, Charles Dawson authored at least 18 papers between 2020 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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Bibliography

2024

Active Disruption Avoidance and Trajectory Design for Tokamak Ramp-downs with Neural Differential Equations and Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2024

2023

Shield Model Predictive Path Integral: A Computationally Efficient Robust MPC Method Using Control Barrier Functions.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., November, 2023

Safe Control With Learned Certificates: A Survey of Neural Lyapunov, Barrier, and Contraction Methods for Robotics and Control.

[BibT_eX]

[DOI]

Charles Dawson

Sicun Gao

Chuchu Fan

IEEE Trans. Robotics, June, 2023

Model-Free Neural Fault Detection and Isolation for Safe Control.

[BibT_eX]

[DOI]

IEEE Control. Syst. Lett., 2023

Learning Safe Control for Multi-Robot Systems: Methods, Verification, and Open Challenges.

[BibT_eX]

[DOI]

CoRR, 2023

Adversarial optimization leads to over-optimistic security-constrained dispatch, but sampling can help.

[BibT_eX]

[DOI]

Charles Dawson

Chuchu Fan

CoRR, 2023

Shield Model Predictive Path Integral: A Computationally Efficient Robust MPC Approach Using Control Barrier Functions.

[BibT_eX]

[DOI]

CoRR, 2023

Chance-Constrained Trajectory Optimization for High-DOF Robots in Uncertain Environments.

[BibT_eX]

[DOI]

CoRR, 2023

Enforcing safety for vision-based controllers via Control Barrier Functions and Neural Radiance Fields.

[BibT_eX]

[DOI]

Mukun Tong

Charles Dawson

Chuchu Fan

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

A Bayesian approach to breaking things: efficiently predicting and repairing failure modes via sampling.

[BibT_eX]

[DOI]

Charles Dawson

Chuchu Fan

Proceedings of the Conference on Robot Learning, 2023

2022

Learning Safe, Generalizable Perception-Based Hybrid Control With Certificates.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., 2022

Barrier functions enable safety-conscious force-feedback control.

[BibT_eX]

[DOI]

CoRR, 2022

Safe Control with Learned Certificates: A Survey of Neural Lyapunov, Barrier, and Contraction methods.

[BibT_eX]

[DOI]

Charles Dawson

Sicun Gao

Chuchu Fan

CoRR, 2022

Certifiable Robot Design Optimization using Differentiable Programming.

[BibT_eX]

[DOI]

Charles Dawson

Chuchu Fan

Proceedings of the Robotics: Science and Systems XVIII, New York City, NY, USA, June 27, 2022

Robust Counterexample-guided Optimization for Planning from Differentiable Temporal Logic.

[BibT_eX]

[DOI]

Charles Dawson

Chuchu Fan

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

2021

Safe Nonlinear Control Using Robust Neural Lyapunov-Barrier Functions.

[BibT_eX]

[DOI]

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020

Fast Certification of Collision Probability Bounds with Uncertain Convex Obstacles.

[BibT_eX]

[DOI]

Charles Dawson

Andreas G. Hofmann

Brian C. Williams

CoRR, 2020

Provably Safe Trajectory Optimization in the Presence of Uncertain Convex Obstacles.

[BibT_eX]

[DOI]

Charles Dawson

Ashkan Jasour

Andreas G. Hofmann

Brian Charles Williams

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Charles Dawson

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