WOLF: A modular estimation framework for robotics based on factor graphs

Autor:	Sola, Joan, Vallve, Joan, Casals, Joaquim, Deray, Jeremie, Fourmy, Mederic, Atchuthan, Dinesh, Corominas-Murtra, Andreu, Andrade-Cetto, Juan
Rok vydání:	2021
Předmět:	Computer Science - Robotics
Druh dokumentu:	Working Paper
Popis:	This paper introduces WOLF, a C++ estimation framework based on factor graphs and targeted at mobile robotics. WOLF can be used beyond SLAM to handle self-calibration, model identification, or the observation of dynamic quantities other than localization. The architecture of WOLF allows for a modular yet tightly-coupled estimator. Modularity is enhanced via reusable plugins that are loaded at runtime depending on application setup. This setup is achieved conveniently through YAML files, allowing users to configure a wide range of applications without the need of writing or compiling code. Most procedures are coded as abstract algorithms in base classes with varying levels of specialization. Overall, all these assets allow for coherent processing and favor code re-usability and scalability. WOLF can be used with ROS, and is made publicly available and open to collaboration. Comment: 8 pages, 12 figures. v1: removed repository link. v2: add TERRINET thanks. v3: full review, authors addition and fix. v4: Fix one citation
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2110.12919 Zobrazit plný text záznamu View this record from Arxiv