4 citations · 6 across the 3 of their papers we have counts for
10 papers
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…
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…
Robust MADER: Decentralized and Asynchronous Multiagent Trajectory Planner Robust to Communication Delay
Kota Kondo, Jesus Tordesillas, Reinaldo Figueroa +4
Although communication delays can disrupt multiagent systems, most of the existing multiagent trajectory planners lack a strategy to address this issue. State-of-the-art approaches…
Global Data Association for SLAM with 3D Grassmannian Manifold Objects
Parker C. Lusk, Jonathan P. How
Using pole and plane objects in lidar SLAM can increase accuracy and decrease map storage requirements compared to commonly-used point cloud maps. However, place recognition and ge…