2 citations · 4 across the 7 of their papers we have counts for
7 papers
Reference-Free, Long-Horizon Trajectory Optimization for Aggressive Autonomous Driving in Milliseconds
Prayag Sharma, Jonathan Y. M. Goh, Franck Djeumou
Autonomous vehicles must generate long-horizon and dynamically feasible trajectories in real time-even when operating at the limits of vehicle handling-to ensure safe operation in…
Transcription-Induced Failure Modes in 6-DOF Rocket Landing Trajectory Optimization
Prayag Sharma, Jonathan Y. M. Goh, Behçet Açıkmeşe +1
Solving optimal control problems via large-scale NLP solvers depends on discretizing continuous dynamics. Yet, this transcription step hides critical vulnerabilities-most notably t…
How to Learn and Generalize From Three Minutes of Data: Physics-Constrained and Uncertainty-Aware Neural Stochastic Differential Equations
Franck Djeumou, Cyrus Neary, Ufuk Topcu
We present a framework and algorithms to learn controlled dynamics models using neural stochastic differential equations (SDEs) -- SDEs whose drift and diffusion terms are both par…
Autonomous Drifting with 3 Minutes of Data via Learned Tire Models
Franck Djeumou, Jonathan Y. M. Goh, Ufuk Topcu +1
Near the limits of adhesion, the forces generated by a tire are nonlinear and intricately coupled. Efficient and accurate modelling in this region could improve safety, especially…
Physics-Informed Kernel Embeddings: Integrating Prior System Knowledge with Data-Driven Control
Adam J. Thorpe, Cyrus Neary, Franck Djeumou +2
Data-driven control algorithms use observations of system dynamics to construct an implicit model for the purpose of control. However, in practice, data-driven techniques often req…
Task-Guided IRL in POMDPs that Scales
Franck Djeumou, Christian Ellis, Murat Cubuktepe +2
In inverse reinforcement learning (IRL), a learning agent infers a reward function encoding the underlying task using demonstrations from experts. However, many existing IRL techni…
Learning to Reach, Swim, Walk and Fly in One Trial: Data-Driven Control with Scarce Data and Side Information
Franck Djeumou, Ufuk Topcu
We develop a learning-based control algorithm for unknown dynamical systems under very severe data limitations. Specifically, the algorithm has access to streaming and noisy data o…