4 citations · 9 across the 17 of their papers we have counts for
19 papers
GaussLite: Online Task-Conditioned 3D Gaussian Splatting for Real-Time Robotic Mapping
Annika Thomas, Mason Peterson, Jonathan P. How
Existing 3D Gaussian Splatting (3DGS) systems distribute representation capacity uniformly across a scene, ignoring the fact that many downstream robotic tasks engage only a fracti…
Overlapping Domain Decomposition for Distributed Pose Graph Optimization
Aneesa Sonawalla, Yulun Tian, Jonathan P. How
We present ROBO (Riemannian Overlapping Block Optimization), a distributed and parallel approach to multi-robot pose graph optimization (PGO) based on the idea of overlapping domai…
MIGHTY: Hermite Spline-based Efficient Trajectory Planning
Kota Kondo, Yuwei Wu, Vijay Kumar +1
Hard-constraint trajectory planners often rely on commercial solvers and demand substantial computational resources. Existing soft-constraint methods achieve faster computation, bu…
Distribution Estimation for Global Data Association via Approximate Bayesian Inference
Yixuan Jia, Mason B. Peterson, Qingyuan Li +2
Global data association is an essential prerequisite for robot operation in environments seen at different times or by different robots. Repetitive or symmetric data creates signif…
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…
GRAND-SLAM: Local Optimization for Globally Consistent Large-Scale Multi-Agent Gaussian SLAM
Annika Thomas, Aneesa Sonawalla, Alex Rose +1
3D Gaussian splatting has emerged as an expressive scene representation for RGB-D visual SLAM, but its application to large-scale, multi-agent outdoor environments remains unexplor…
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…
LunarLoc: Segment-Based Global Localization on the Moon
Annika Thomas, Robaire Galliath, Aleksander Garbuz +6
Global localization is necessary for autonomous operations on the lunar surface where traditional Earth-based navigation infrastructure, such as GPS, is unavailable. As NASA advanc…
DYNUS: Uncertainty-aware Trajectory Planner in Dynamic Unknown Environments
Kota Kondo, Mason Peterson, Nicholas Rober +5
This paper introduces DYNUS, an uncertainty-aware trajectory planner designed for dynamic unknown environments. Operating in such settings presents many challenges -- most notably,…
ROMAN: Open-Set Object Map Alignment for Robust View-Invariant Global Localization
Mason B. Peterson, Yixuan Jia, Yulun Tian +2
Global localization is a fundamental capability required for long-term and drift-free robot navigation. However, current methods fail to relocalize when faced with significantly di…
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…
TCAFF: Temporal Consistency for Robot Frame Alignment
Mason B. Peterson, Parker C. Lusk, Antonio Avila +1
In the field of collaborative robotics, the ability to communicate spatial information like planned trajectories and shared environment information is crucial. When no global posit…
CLIPPER: Robust Data Association without an Initial Guess
Parker C. Lusk, Jonathan P. How
Identifying correspondences in noisy data is a critically important step in estimation processes. When an informative initial estimation guess is available, the data association ch…
SOS-Match: Segmentation for Open-Set Robust Correspondence Search and Robot Localization in Unstructured Environments
Annika Thomas, Jouko Kinnari, Parker Lusk +2
We present SOS-Match, a novel framework for detecting and matching objects in unstructured environments. Our system consists of 1) a front-end mapping pipeline using a zero-shot se…
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…
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…