Charles Dawson

Orcid: 0000-0002-8371-5313

Affiliations:
  • Massachusetts Institute of Technology, Cambridge, MA, USA


According to our database1, Charles Dawson authored at least 21 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Online presence:

On csauthors.net:

Bibliography

2024
Learning-Based Bayesian Inference for Testing of Autonomous Systems.
IEEE Robotics Autom. Lett., October, 2024

RADIUM: Predicting and Repairing End-to-End Robot Failures using Gradient-Accelerated Sampling.
CoRR, 2024

Active Disruption Avoidance and Trajectory Design for Tokamak Ramp-downs with Neural Differential Equations and Reinforcement Learning.
CoRR, 2024

Learning safe control for multi-robot systems: Methods, verification, and open challenges.
Annu. Rev. Control., 2024

AutoTAMP: Autoregressive Task and Motion Planning with LLMs as Translators and Checkers.
Proceedings of the IEEE International Conference on Robotics and Automation, 2024

2023
Shield Model Predictive Path Integral: A Computationally Efficient Robust MPC Method Using Control Barrier Functions.
IEEE Robotics Autom. Lett., November, 2023

Safe Control With Learned Certificates: A Survey of Neural Lyapunov, Barrier, and Contraction Methods for Robotics and Control.
IEEE Trans. Robotics, June, 2023

Model-Free Neural Fault Detection and Isolation for Safe Control.
IEEE Control. Syst. Lett., 2023

Adversarial optimization leads to over-optimistic security-constrained dispatch, but sampling can help.
CoRR, 2023

Shield Model Predictive Path Integral: A Computationally Efficient Robust MPC Approach Using Control Barrier Functions.
CoRR, 2023

Chance-Constrained Trajectory Optimization for High-DOF Robots in Uncertain Environments.
CoRR, 2023

Enforcing safety for vision-based controllers via Control Barrier Functions and Neural Radiance Fields.
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.
Proceedings of the Conference on Robot Learning, 2023

2022
Learning Safe, Generalizable Perception-Based Hybrid Control With Certificates.
IEEE Robotics Autom. Lett., 2022

Barrier functions enable safety-conscious force-feedback control.
CoRR, 2022

Safe Control with Learned Certificates: A Survey of Neural Lyapunov, Barrier, and Contraction methods.
CoRR, 2022

Certifiable Robot Design Optimization using Differentiable Programming.
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.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

2021
Safe Nonlinear Control Using Robust Neural Lyapunov-Barrier Functions.
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.
CoRR, 2020

Provably Safe Trajectory Optimization in the Presence of Uncertain Convex Obstacles.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020


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