activity
20242026
collaborators

6 papers

cs.RO2026

X-OP: Cross-Morphology Whole-Body Teleoperation via MPC Retargeting

Jen-Wei Wang, Sarthak Kaingade, Andrea Tagliabue +1

Whole-body teleoperation is essential for scalable robot data collection in loco-manipulation tasks, yet existing approaches relying on exoskeleton suits or multi-camera setups imp…

cs.RO2025

Aerobatic maneuvers in insect-scale flapping-wing aerial robots via deep-learned robust tube model predictive control

Yi-Hsuan Hsiao, Andrea Tagliabue, Owen Matteson +4

Aerial insects exhibit highly agile maneuvers such as sharp braking, saccades, and body flips under disturbance. In contrast, insect-scale aerial robots are limited to tracking non…

cs.RO2025

Terrain-aware Low Altitude Path Planning

Yixuan Jia, Andrea Tagliabue, Annika Thomas +2

In this paper, we study the problem of generating low-altitude path plans for nap-of-the-earth (NOE) flight in real time with only RGB images from onboard cameras and the vehicle p…

cs.RO2025

PRIMER: Perception-Aware Robust Learning-based Multiagent Trajectory Planner

Kota Kondo, Claudius T. Tewari, Andrea Tagliabue +4

In decentralized multiagent trajectory planners, agents need to communicate and exchange their positions to generate collision-free trajectories. However, due to localization error…

cs.RO2024

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…

cs.RO2024

CGD: Constraint-Guided Diffusion Policies for UAV Trajectory Planning

Kota Kondo, Andrea Tagliabue, Xiaoyi Cai +4

Traditional optimization-based planners, while effective, suffer from high computational costs, resulting in slow trajectory generation. A successful strategy to reduce computation…