AEROS: AdaptivE RObust Least-Squares for Graph-Based SLAM

Autor: Milad Ramezani, Matias Mattamala, Maurice Fallon

Publikováno v: Frontiers in Robotics and AI, Vol 9 (2022)

In robot localisation and mapping, outliers are unavoidable when loop-closure measurements are taken into account. A single false-positive loop-closure can have a very negative impact on SLAM problems causing an inferior trajectory to be produced or

Externí odkaz: https://doaj.org/article/63d79bf3d07d4cd1b498264a8435d121

Observability-aware online multi-lidar extrinsic calibration

Autor: Sandipan Das, Ludvig af Klinteberg, Maurice Fallon, Saikat Chatterjee

Accurate and robust extrinsic calibration is necessary for deploying autonomous systems which need multiple sensors for perception. In this paper, we present a robust system for real-time extrinsic calibration of multiple lidars in vehicle base frame

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::468ed55f148d40e4cecfa970ce7298e1
http://arxiv.org/abs/2212.09579

Navigating by touch: haptic Monte Carlo localization via geometric sensing and terrain classification

Autor: Michał Nowicki, Marco Camurri, Maurice Fallon, Russell Buchanan, Krzysztof Walas, Jakub Bednarek

Publikováno v: Buchanan, R, Bednarek, J, Camurri, M, Nowicki, M R, Walas, K & Fallon, M 2021, ' Navigating by touch : Haptic Monte Carlo localization via geometric sensing and terrain classification ', Autonomous Robots, vol. 45, no. 6, pp. 843-857 . https://doi.org/10.1007/s10514-021-10013-w

Legged robot navigation in extreme environments can hinder the use of cameras and laser scanners due to darkness, air obfuscation or sensor damage. In these conditions, proprioceptive sensing will continue to work reliably. In this paper, we propose

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::694cc0a14f9655dbbee38ae1a1240b5f
https://doi.org/10.1007/s10514-021-10013-w

Team CERBERUS Wins the DARPA Subterranean Challenge: Technical Overview and Lessons Learned

Autor: Marco Tranzatto, Mihir Kulkarni, Victor Reijgwart, Benoit Casseau, Timon Homberger, Paolo De Petris, Lionel Ott, Wayne Tubby, Gabriel Waibel, Huan Nguyen, Cesar Cadena, Mihir Dharmadhikari, Russell Buchanan, Lorenz Wellhausen, Nikhil Khedekar, Olov Andersson, Lintong Zhang, Takahiro Miki, Tung Dang, Matias Mattamala, Markus Montenegro, Konrad Meyer, Lukas Bernreiter, Xiangyu Wu, Adrien Briod, Mark Mueller, Maurice Fallon, Roland Siegwart, Marco Hutter, Kostas Alexis, Marco Camurri, Shehryar Khattak, Frank Mascarich, Patrick Pfreundschuh, David Wisth, Samuel Zimmermann

Publikováno v: Web of Science

This article presents the CERBERUS robotic system-of-systems, which won the DARPA Subterranean Challenge Final Event in 2021. The Subterranean Challenge was organized by DARPA with the vision to facilitate the novel technologies necessary to reliably

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::66c702eb37fa951ae6621a93f0b98aba
http://arxiv.org/abs/2207.04914

Unsupervised learning of terrain representations for haptic Monte Carlo localization

Autor: Mikolaj Lysakowski, Michal R. Nowicki, Russell Buchanan, Marco Camurri, Maurice Fallon, Krzysztof Walas

Haptic sensing has recently been used effectively for legged robot localization in extreme scenarios where cam-eras and LiDAR might fail, such as dusty mines and foggy sewers. However, existing haptic sensing mainly relies on supervised classificatio

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5f2988468e16a5df5f96d62f434c241a
https://ora.ox.ac.uk/objects/uuid:5729c2b2-23f5-4df5-b775-e2b595bf3c65