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Luís Garrote

4 accepted papers

2024

PointNetPGAP-SLC: A 3D LiDAR-Based Place Recognition Approach With Segment-Level Consistency Training for Mobile Robots in Horticulture

RA-L 2024

3D LiDAR-based place recognition remains largely underexplored in horticultural environments, which present unique challenges due to their semi-permeable nature to laser beams. This characteristic often results in highly similar LiDAR scans from adjacent rows, leading to descriptor ambiguity and, co

Cited by 8SourceScholar
2021

A Deep Learning-based Indoor Scene Classification Approach Enhanced with Inter-Object Distance Semantic Features

IROS 2021poster

Convolutional Neural Networks (CNNs) have been increasingly applied in visual classification tasks by replacing hand-crafted features with deep features. However, problems such as inter-class similarity and intra-class variation led to the need of obtaining more descriptive features. To accomplish t…

Cited by 15SourceScholar
2019

Mobile Robot Localization with Reinforcement Learning Map Update Decision aided by an Absolute Indoor Positioning System

IROS 2019poster

This paper introduces a new mobile robot localization solution consisting of two main modules: a Particle-Filter based Localization (PFL) and a Reinforcement-Learning based map updating, integrating relative measurements and absolute indoor positioning sensor (A-IPS) data. Concerning localization us…

Cited by 17SourceScholar
2018

HMAPs - Hybrid Height- Voxel Maps for Environment Representation

IROS 2018poster

This paper presents a hybrid 3D-like grid-based mapping approach, that we called HMAP, used as a reliable and efficient 3D representation of the environment surrounding a mobile robot. Considering 3D point-clouds as input data, the proposed mapping approach addresses the representation of height-vox…

Cited by 5SourceScholar