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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Place Recognition in Forests With Urquhart Tessellations

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Author(s):
Nardari, V, Guilherme ; Cohen, Avraham [1] ; Chen, Steven W. [1, 2] ; Liu, Xu [1] ; Arcot, Vaibhav [1, 2] ; Romero, Roseli A. F. [3] ; Kumar, Vijay [1]
Total Authors: 7
Affiliation:
[1] Nardari, Guilherme, V, Univ Penn, GRASP Lab, Philadelphia, PA 19104 - USA
[2] Treeswift, Philadelphia, PA 19104 - USA
[3] Nardari, Guilherme, V, Univ Sao Paulo, Robot Learning Lab, BR-13566590 Sao Carlos, SP - Brazil
Total Affiliations: 3
Document type: Journal article
Source: IEEE ROBOTICS AND AUTOMATION LETTERS; v. 6, n. 2, p. 279-286, APR 2021.
Web of Science Citations: 0
Abstract

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 closure detection experiments in simulation and real-world data map-merging from different flights of an Unmanned Aerial Vehicle (UAV) in a pine tree forest and show that our method outperforms state-of-the-art approaches in accuracy and robustness. (AU)

FAPESP's process: 14/50851-0 - INCT 2014: National Institute of Science and Technology for Cooperative Autonomous Systems Applied in Security and Environment
Grantee:Marco Henrique Terra
Support type: Research Projects - Thematic Grants
FAPESP's process: 18/24526-5 - Estimation of crop structure and health using heterogeneous robots
Grantee:Guilherme Vicentim Nardari
Support type: Scholarships abroad - Research Internship - Doctorate (Direct)