Demos

Adaptive-resolution Mapping

Adaptive-resolution octree-based volumetric SLAM [1].

MID-Fusion

MID-Fusion: Octree-based Object-Level Multi-Instance Dynamic SLAM [2‌‌].

InteriorNet

InteriorNet: Mega-scale Multi-sensor Photo-realistic Indoor Scenes Dataset [3‌‌‌].

Downloads and further information at https://interiornet.org/ .

Fusion++

Fusion++: Volumetric Object-Level SLAM [4‌‌‌‌].

In collaboration with the Dyson Robotics Lab.

Fully Autonomous Multicopters

Fully autonomous MAV flight and landing on a moving target using visual-inertial estimation and model-predictive control [5‌‌‌‌‌].

In collaboration within Aerial Additive Manufacturing (the Aerial Robotics Lab)

Dense RGB-D-Inertial SLAM with Map Deformations

Dense RGB-D-Inertial SLAM with Map Deformations [6‌‌‌‌‌‌].

In collaboration with the Dyson Robotics Lab.

SemanticFusion

SemanticFusion: Dense 3D Semantic Mapping with Convolutional Neural Networks [7‌‌‌‌‌‌‌].

In collaboration with the Dyson Robotics Lab.

Monocular, Real-Time Surface Reconstruction

Monocular, Real-Time Surface Reconstruction using Dynamic Level of Detail [8‌‌‌‌‌‌‌‌].

In collaboration with the Dyson Robotics Lab.

ElasticFusion

ElasticFusion: Real-Time Dense SLAM and Light Source Estimation [9‌‌‌‌‌‌‌‌‌].

In collaboration with the Dyson Robotics Lab.

OKVIS: Open Keyframe-based Visual Inertial SLAM

 

Keyframe-Based Visual-Inertial Odometry Using Nonlinear Optimisation [10‌‌‌‌‌‌‌‌‌‌],[11‌‌‌‌‌‌‌‌‌‌‌]

Code available under BSD, see software.

BRISK

Binary Robust Invariant Scalable Keypoints [12‌‌‌‌‌‌‌‌‌‌‌‌]

Code available under BSD, see software.

Solar Aeroplane Operations

senseSoar solar aeroplane: first test flights.

 


[10‌‌‌‌‌‌‌‌‌‌] Stefan Leutenegger, Paul Timothy Furgale, Vincent Rabaud, Margarita Chli, Kurt Konolige, Roland Siegwart, Keyframe-Based Visual-Inertial SLAM using Nonlinear Optimization., Robotics: Science and Systems, 2013
[11‌‌‌‌‌‌‌‌‌‌‌] Stefan Leutenegger, Simon Lynen, Michael Bosse, Roland Siegwart, Paul Furgale, Keyframe-based visual–inertial odometry using nonlinear optimization, The International Journal of Robotics Research, pp.0278364914554813, 2014
[12‌‌‌‌‌‌‌‌‌‌‌‌] Stefan Leutenegger, Margarita Chli, Roland Yves Siegwart, BRISK: Binary robust invariant scalable keypoints, Computer Vision (ICCV), 2011 IEEE International Conference on, pp.2548–2555, 2011
[2‌‌] Binbin Xu, Wenbin Li, Dimos Tzoumanikas, Michael Bloesch, Andrew Davison, Stefan Leutenegger, MID-Fusion: Octree-based Object-Level Multi-Instance Dynamic SLAM, arXiv preprint arXiv:1812.07976, 2018
[3‌‌‌] Wenbin Li, Sajad Saeedi, John McCormac, Ronald Clark, Dimos Tzoumanikas, Qing Ye, Yuzhong Huang, Rui Tang, Stefan Leutenegger, InteriorNet: Mega-scale Multi-sensor Photo-realistic Indoor Scenes Dataset, British Machine Vision Conference (BMVC), 2018
[4‌‌‌‌] John McCormac, Ronald Clark, Michael Bloesch, Andrew Davison, Stefan Leutenegger, Fusion++: Volumetric Object-Level SLAM, 2018
[5‌‌‌‌‌] Dimos Tzoumanikas, Wenbin Li, Marius Grimm, Ketao Zhang, Mirko Kovac, Stefan Leutenegger, Fully autonomous MAV flight and landing on a moving target using visual-inertial estimation and model-predictive control, Journal of Field Robotics, 2018
[6‌‌‌‌‌‌] Tristan Laidlow, Michael Bloesch, Wenbin Li, Stefan Leutenegger, Dense RGB-D-Inertial SLAM with Map Deformations, Intelligent Robots and Systems (IROS), 2017 IEEE/RSJ International Conference on, 2017
[7‌‌‌‌‌‌‌] J McCormac, A Handa, A Davison, S Leutenegger, SemanticFusion: Dense 3D Semantic Mapping with Convolutional Neural Networks, 2016
[8‌‌‌‌‌‌‌‌] J Zienkiewicz, C Tsiotsios, AJ Davison, S Leutenegger, Monocular, Real-Time Surface Reconstruction using Dynamic Level of Detail, 2016
[9‌‌‌‌‌‌‌‌‌] T. Whelan, R. F. Salas-Moreno, B. Glocker, A. J. Davison, S. Leutenegger, ElasticFusion: Real-Time Dense SLAM and Light Source Estimation, Intl. J. of Robotics Research, IJRR, 2016