62 citations · 79 across the 11 of their papers we have counts for
11 papers
Multistep Belief Space Dynamics Learning For Risk-Aware Control
Jason Gibson, Bogdan Vlahov, Patrick Spieler +1
As autonomous vehicles move from a simplified research setting to practical use, there exists a large gap between the dynamic behavior of a human driving and an autonomous system.…
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…
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…
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,…
Low Frequency Sampling in Model Predictive Path Integral Control
Bogdan Vlahov, Jason Gibson, David D. Fan +3
Sampling-based model-predictive controllers have become a powerful optimization tool for planning and control problems in various challenging environments. In this paper, we show h…
A Multi-step Dynamics Modeling Framework For Autonomous Driving In Multiple Environments
Jason Gibson, Bogdan Vlahov, David Fan +4
Modeling dynamics is often the first step to making a vehicle autonomous. While on-road autonomous vehicles have been extensively studied, off-road vehicles pose many challenging m…
Data-Augmentation for Graph Neural Network Learning of the Relaxed Energies of Unrelaxed Structures
Jason B. Gibson, Ajinkya C. Hire, Richard G. Hennig
Computational materials discovery has continually grown in utility over the past decade due to advances in computing power and crystal structure prediction algorithms (CSPA). Howev…
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…
Robust Model Predictive Path Integral Control: Analysis and Performance Guarantees
Manan Gandhi, Bogdan Vlahov, Jason Gibson +2
In this paper we propose a novel decision making architecture for Robust Model Predictive Path Integral control (RMPPI) and investigate its performance guarantees and applicability…
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…
Aggressive Perception-Aware Navigation using Deep Optical Flow Dynamics and PixelMPC
Keuntaek Lee, Jason Gibson, Evangelos A. Theodorou
Recently, vision-based control has gained traction by leveraging the power of machine learning. In this work, we couple a model predictive control (MPC) framework to a visual pipel…