Roseli A. F. Romero — accepted AI-conference papers

2022

Large-Scale Autonomous Flight With Real-Time Semantic SLAM Under Dense Forest Canopy

Xu Liu, Guilherme V. Nardari, Fernando Cladera Ojeda, Yuezhan Tao, Alex Zhou, Thomas Donnelly +5

RA-L 2022

Semantic maps represent the environment using a set of semantically meaningful objects. This representation is storage-efficient, less ambiguous, and more informative, thus facilitating large-scale autonomy and the acquisition of actionable information in highly unstructured, GPS-denied environments

Cited by 99 Source ↗Scholar ↗

2021

Place Recognition in Forests With Urquhart Tessellations

Guilherme V. Nardari, Avraham Cohen, Steven W. Chen, Xu Liu, Vaibhav Arcot, Roseli A. F. Romero +1

RA-L 2021

In this letter, we present a novel descriptor based on Urquhart tessellations derived from the position of trees in a forest. We propose a framework that uses these descriptors to detect previously seen observations and landmark correspondences, even with partial overlap and noise. We run loop closu

Cited by 19 Source ↗code ↗Scholar ↗