Matías Mattamala

Matías Mattamala

University of Oxford

H-index: 8

Europe-United Kingdom

About Matías Mattamala

Matías Mattamala, With an exceptional h-index of 8 and a recent h-index of 8 (since 2020), a distinguished researcher at University of Oxford, specializes in the field of Robotics, Computer Vision, Navigation.

His recent articles reflect a diverse array of research interests and contributions to the field:

Wild Visual Navigation: Fast Traversability Learning via Pre-Trained Models and Online Self-Supervision

Online Tree Reconstruction and Forest Inventory on a Mobile Robotic System

Evaluation and Deployment of LiDAR-based Place Recognition in Dense Forests

Exosense: A Vision-Centric Scene Understanding System For Safe Exoskeleton Navigation

SiLVR: Scalable Lidar-Visual Reconstruction with Neural Radiance Fields for Robotic Inspection

Tree Instance Segmentation and Traits Estimation for Forestry Environments Exploiting LiDAR Data Collected by Mobile Robots

Autonomous Forest Inventory with Legged Robots: System Design and Field Deployment

Resilient Legged Local Navigation: Learning to Traverse with Compromised Perception End-to-End

Matías Mattamala Information

University

Position

DPhil student Oxford Robotics Institute

Citations(all)

270

Citations(since 2020)

256

Cited By

45

hIndex(all)

8

hIndex(since 2020)

8

i10Index(all)

8

i10Index(since 2020)

7

Email

University Profile Page

Google Scholar

Matías Mattamala Skills & Research Interests

Robotics

Computer Vision

Navigation

Top articles of Matías Mattamala

Wild Visual Navigation: Fast Traversability Learning via Pre-Trained Models and Online Self-Supervision

arXiv preprint arXiv:2404.07110

2024/4/10

Online Tree Reconstruction and Forest Inventory on a Mobile Robotic System

arXiv preprint arXiv:2403.17622

2024/3/26

Evaluation and Deployment of LiDAR-based Place Recognition in Dense Forests

arXiv preprint arXiv:2403.14326

2024/3/21

Exosense: A Vision-Centric Scene Understanding System For Safe Exoskeleton Navigation

arXiv preprint arXiv:2403.14320

2024/3/21

SiLVR: Scalable Lidar-Visual Reconstruction with Neural Radiance Fields for Robotic Inspection

arXiv preprint arXiv:2403.06877

2024/3/11

Tree Instance Segmentation and Traits Estimation for Forestry Environments Exploiting LiDAR Data Collected by Mobile Robots

2024

Autonomous Forest Inventory with Legged Robots: System Design and Field Deployment

arXiv preprint arXiv:2404.14157

2024/4/22

Resilient Legged Local Navigation: Learning to Traverse with Compromised Perception End-to-End

arXiv preprint arXiv:2310.03581

2023/10/5

MEM: Multi-Modal Elevation Mapping for Robotics and Learning

2023/10/1

Vision-based legged robot navigation: localisation, local planning, learning

2023

Language-EXtended Indoor SLAM (LEXIS): A Versatile System for Real-time Visual Scene Understanding

arXiv preprint arXiv:2309.15065

2023/9/26

Fast Traversability Estimation for Wild Visual Navigation

arXiv preprint arXiv:2305.08510

2023/5/15

Strategies for large scale elastic and semantic LiDAR reconstruction

Robotics and Autonomous Systems

2022/9/1

Aeros: Adaptive robust least-squares for graph-based slam

Frontiers in Robotics and AI

2022/4/1

An efficient locally reactive controller for safe navigation in visual teach and repeat missions

IEEE Robotics and Automation Letters

2022/1/14

Scalable and elastic lidar reconstruction in complex environments through spatial analysis

2021/8/31

Learning camera performance models for active multi-camera visual teach and repeat

2021

The newer college dataset: Handheld lidar, inertial and vision with ground truth

arXiv

2020

Adaptive manipulator control using active inference with precision learning

UKRAS20 Conference:” Robots into the real world” Proceedings, Lincoln, United Kingdom

2020/5/6

See List of Professors in Matías Mattamala University(University of Oxford)

Co-Authors

academic-engine