pyslam v2.1 is available
I am happy to share the new version of pyslam: v2.1. It comes with new improvements and the following new
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Luigi Freda
Robotics & Computer Vision Engineer, PhD
SLAM
PLVS code released
I am happy to release the code of my project PLVS. PLVS is a real-time system that leverages sparse RGB-D and Stereo SLAM, volumetric mapping, and
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slamplay is ready!
If you love to play with SLAM like me, I shared slamplay on github: https://github.com/luigifreda/slamplay. slamplay is a collection of powerful
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My new pySLAM v2 is out!
I am excited to release pySLAM v2. The new version allows you to play with SLAM techniques, visual-odometry, keyframes, bundle-adjustment,
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Member of the Program Committee of SAC 2020-IRMAS Track
I’m very pleased to serve as a member of the Program Committee of the IRMAS – Intelligent Robotics and Multi-Agent
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Visual Perception and Spatial Computing
On February 2019, I was the teacher of the course Visual Perception and Spatial Computing in the Advanced School of AI. This school
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3Dpatrolling – 3D Multi-Robot Patrolling with a Two-Level Coordination Strategy
I am very excited to release the paper 3D Multi-Robot Patrolling with a Two-Level Coordination Strategy (just appeared in Autonomous Robots) and
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PLVS: An Open-Source RGB-D and Stereo SLAM for volumetric reconstruction and 3D incremental segmentation
I am working hard during my free time and having fun with PLVS to finalize the outcoming paper: PLVS: An
Read morePLVS: An open-source SLAM system with Points, Lines, Volumetric mapping and 3D incremental Segmentation
PLVS(*) is a real-time system that leverages sparse RGB-D and Stereo SLAM, volumetric mapping, and 3D unsupervised incremental segmentation. PLVS
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@ Inglobe Technologies
From May 2018 I am Chief Research Officer at Inglobe Technologies. I will lead R&D activities on Computer Vision, Machine
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Fourth TRADR Evaluation Exercise in Rotterdam with GB Firefighters
From November 6th to November 17th, I took part to the fourth TRADR Evaluation Exercise in Rotterdam. The full TRADR system was evaluated by the GB firefighters end-users
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TRADR on EuroNews
The TRADR EU project is on Euronews. The video report shows the simulated disaster scene we used in the last
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CNN-SLAM: Real-time dense monocular SLAM with learned depth prediction
In this page, the Authors K. Tateno, F. Tombari, I. Laina and N. Navab present the following paper in which CNNs are used
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RGBDTAM: A Cost-Effective and Accurate RGB-D Tracking and Mapping System
In this post, Alejo Concha Belenguer presents his new work RGBDTAM. This is a direct SLAM pipeline that runs in real-time and
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Best Late Breaking Report at SSRR 2016
Our recent work with ETHZ was awarded Best Late Breaking Report at SSRR 2016 “3D Localization, Mapping and Path Planning for
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