20 citations · 43 across the 20 of their papers we have counts for
23 papers
Ionic gradients shape the spatial organization and dynamics of supramolecular polymers
Claudio Perego, Annalisa Cardellini, Andrea Tagliabue +1
Living supramolecular materials such as microtubules and actin filaments assemble and function in dynamic, heterogeneous environments, subject to chemical concentration gradients.…
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…
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…
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…
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…
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…
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…
Output Feedback Tube MPC-Guided Data Augmentation for Robust, Efficient Sensorimotor Policy Learning
Andrea Tagliabue, Jonathan P. How
Imitation learning (IL) can generate computationally efficient sensorimotor policies from demonstrations provided by computationally expensive model-based sensing and control algor…
Robust, High-Rate Trajectory Tracking on Insect-Scale Soft-Actuated Aerial Robots with Deep-Learned Tube MPC
Andrea Tagliabue, Yi-Hsuan Hsiao, Urban Fasel +4
Accurate and agile trajectory tracking in sub-gram Micro Aerial Vehicles (MAVs) is challenging, as the small scale of the robot induces large model uncertainties, demanding robust…
Demonstration-Efficient Guided Policy Search via Imitation of Robust Tube MPC
Andrea Tagliabue, Dong-Ki Kim, Michael Everett +1
We propose a demonstration-efficient strategy to compress a computationally expensive Model Predictive Controller (MPC) into a more computationally efficient representation based o…
Model-free online motion adaptation for energy efficient flights of multicopters
Xiangyu Wu, Jun Zeng, Andrea Tagliabue +1
Limited flight distance and time is a common problem for multicopters. We propose a method for finding the optimal speed and sideslip angle of a multicopter flying a given path to…
Airflow-Inertial Odometry for Resilient State Estimation on Multirotors
Andrea Tagliabue, Jonathan P. How
We present a dead reckoning strategy for increased resilience to position estimation failures on multirotors, using only data from a low-cost IMU and novel, bio-inspired airflow se…
NeBula: Quest for Robotic Autonomy in Challenging Environments; TEAM CoSTAR at the DARPA Subterranean Challenge
Ali Agha, Kyohei Otsu, Benjamin Morrell +69
This paper presents and discusses algorithms, hardware, and software architecture developed by the TEAM CoSTAR (Collaborative SubTerranean Autonomous Robots), competing in the DARP…
LION: Lidar-Inertial Observability-Aware Navigator for Vision-Denied Environments
Andrea Tagliabue, Jesus Tordesillas, Xiaoyi Cai +4
State estimation for robots navigating in GPS-denied and perceptually-degraded environments, such as underground tunnels, mines and planetary subsurface voids, remains challenging…
The Shapeshifter: a Morphing, Multi-Agent,Multi-Modal Robotic Platform for the Exploration of Titan (preprint version)
Ali-akbar Agha-mohammadi, Andrea Tagliabue, Stephanie Schneider +8
In this report for the Nasa NIAC Phase I study, we present a mission architecture and a robotic platform, the Shapeshifter, that allow multi-domain and redundant mobility on Saturn…
Touch the Wind: Simultaneous Airflow, Drag and Interaction Sensing on a Multirotor
Andrea Tagliabue, Aleix Paris, Suhan Kim +3
Disturbance estimation for Micro Aerial Vehicles (MAVs) is crucial for robustness and safety. In this paper, we use novel, bio-inspired airflow sensors to measure the airflow actin…
Shapeshifter: A Multi-Agent, Multi-Modal Robotic Platform for Exploration of Titan
Andrea Tagliabue, Stephanie Schneider, Marco Pavone +1
In this paper we present a mission architecture and a robotic platform, the Shapeshifter, that allow multi-domain and redundant mobility on Saturn's moon Titan, and potentially oth…
Robust Collaborative Object Transportation Using Multiple MAVs
Andrea Tagliabue, Mina Kamel, Roland Siegwart +1
Collaborative object transportation using multiple Micro Aerial Vehicles (MAVs) with limited communication is a challenging problem. In this paper we address the problem of multipl…
Collaborative Object Transportation Using MAVs via Passive Force Control
Andrea Tagliabue, Mina Kamel, Sebastian Verling +2
This paper shows a strategy based on passive force control for collaborative object transportation using Micro Aerial Vehicles (MAVs), focusing on the transportation of a bulky obj…