Publications (14)
Variational Inference MPC using Tsallis Divergence
Ziyi Wang, Oswin So, Jason Gibson +4
In this paper, we provide a generalized framework for Variational Inference-Stochastic Optimal Control by using thenon-extensive Tsallis divergence. By incorporating the deformed e…
Meta-Learning Online Dynamics Model Adaptation in Off-Road Autonomous Driving
Jacob Levy, Jason Gibson, Bogdan Vlahov +4
High-speed off-road autonomous driving presents unique challenges due to complex, evolving terrain characteristics and the difficulty of accurately modeling terrain-vehicle interac…
Machine-learning interatomic potential for AlN for epitaxial simulation
Nicholas Taormina, Emir Bilgili, Jason Gibson +3
A machine learned interatomic potential for AlN was developed using the ultra-fast force field (UF3) methodology. A strong agreement with density functional theory calculations in…
MPPI-Generic: A CUDA Library for Stochastic Trajectory Optimization
Bogdan Vlahov, Jason Gibson, Manan Gandhi +1
This paper introduces a new C++/CUDA library for GPU-accelerated stochastic optimization called MPPI-Generic. It provides implementations of Model Predictive Path Integral control,…
Dynamics Modeling using Visual Terrain Features for High-Speed Autonomous Off-Road Driving
Jason Gibson, Anoushka Alavilli, Erica Tevere +2
Rapid autonomous traversal of unstructured terrain is essential for scenarios such as disaster response, search and rescue, or planetary exploration. As a vehicle navigates at the…
Approximate Inverse Reinforcement Learning from Vision-based Imitation Learning
Keuntaek Lee, Bogdan Vlahov, Jason Gibson +2
In this work, we present a method for obtaining an implicit objective function for vision-based navigation. The proposed methodology relies on Imitation Learning, Model Predictive…