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Antoni Rosinol

7 accepted papers

2023

NeRF-SLAM: Real-Time Dense Monocular SLAM with Neural Radiance Fields

IROS 2023poster

We propose a novel geometric and photometric 3D mapping pipeline for accurate and real-time scene reconstruction from casually taken monocular images. To achieve this, we leverage recent advances in dense monocular SLAM and real-time hierarchical volumetric neural radiance fields. Our insight is tha…

Cited by 317SourcecodeScholar
2022

LAMP 2.0: A Robust Multi-Robot SLAM System for Operation in Challenging Large-Scale Underground Environments

RA-L 2022

Search and rescue with a team of heterogeneous mobile robots in unknown and large-scale underground environments requires high-precision localization and mapping. This crucial requirement is faced with many challenges in complex and perceptually-degraded subterranean environments, as the onboard per

Cited by 154SourceScholar
2020

3D Dynamic Scene Graphs: Actionable Spatial Perception with Places, Objects, and Humans

RSS 2020poster

We present a unified representation for actionable spatial perception: 3D Dynamic Scene Graphs. Scene graphs are directed graphs where nodes represent entities in the scene (e.g., objects, walls, rooms), and edges represent relations (e.g., inclusion, adjacency) among nodes. Dynamic scene graphs (DS…

2020

Kimera: an Open-Source Library for Real-Time Metric-Semantic Localization and Mapping

ICRA 2020poster

We provide an open-source C++ library for real-time metric-semantic visual-inertial Simultaneous Localization And Mapping (SLAM). The library goes beyond existing visual and visual-inertial SLAM libraries (e.g., ORB-SLAM, VINS-Mono, OKVIS, ROVIO) by enabling mesh reconstruction and semantic labeling…

Cited by 713SourcecodeScholar
2020

Primal-Dual Mesh Convolutional Neural Networks

NeurIPS 2020poster

Recent works in geometric deep learning have introduced neural networks that allow performing inference tasks on three-dimensional geometric data by defining convolution --and sometimes pooling-- operations on triangle meshes. These methods, however, either consider the input mesh as a graph, and do…

2019

Incremental Visual-Inertial 3D Mesh Generation with Structural Regularities

ICRA 2019poster

Visual-Inertial Odometry (VIO) algorithms typically rely on a point cloud representation of the scene that does not model the topology of the environment. A 3D mesh instead offers a richer, yet lightweight, model. Nevertheless, building a 3D mesh out of the sparse and noisy 3D landmarks triangulated…

Cited by 64SourcecodeScholar