20 citations · 43 across the 20 of their papers we have counts for
5 papers · 1 filter
REAL: Resilience and Adaptation using Large Language Models on Autonomous Aerial Robots
Andrea Tagliabue, Kota Kondo, Tong Zhao +3
Large Language Models (LLMs) pre-trained on internet-scale datasets have shown impressive capabilities in code understanding, synthesis, and general purpose question-and-answering.…
Tube-NeRF: Efficient Imitation Learning of Visuomotor Policies from MPC using Tube-Guided Data Augmentation and NeRFs
Andrea Tagliabue, Jonathan P. How
Imitation learning (IL) can train computationally-efficient sensorimotor policies from a resource-intensive Model Predictive Controller (MPC), but it often requires many samples, l…
PUMA: Fully Decentralized Uncertainty-aware Multiagent Trajectory Planner with Real-time Image Segmentation-based Frame Alignment
Kota Kondo, Claudius T. Tewari, Mason B. Peterson +4
Fully decentralized, multiagent trajectory planners enable complex tasks like search and rescue or package delivery by ensuring safe navigation in unknown environments. However, de…
Efficient Deep Learning of Robust Policies from MPC using Imitation and Tube-Guided Data Augmentation
Andrea Tagliabue, Jonathan P. How
Imitation Learning (IL) can generate computationally efficient policies from demonstrations provided by Model Predictive Control (MPC). However, IL methods often require extensive…
Efficient Deep Learning of Robust, Adaptive Policies using Tube MPC-Guided Data Augmentation
Tong Zhao, Andrea Tagliabue, Jonathan P. How
The deployment of agile autonomous systems in challenging, unstructured environments requires adaptation capabilities and robustness to uncertainties. Existing robust and adaptive…