Although Point Clouds Registration is a very well studied problem, with many different solutions, most of the approaches in the literature aims at aligning two dense point clouds. Instead, we tackle the problem of aligning a dense point cloud with a sparse one: a problem that has to be solved, for example, to merge maps produced by different sensors, such as a vision-based sensor and laser scanner or two different laser-based sensors. The most used approach to point clouds registration, Iterative Closest Point (ICP), is also applicable to this sub-problem. We propose an improvement over the standard ICP data association policy and we called it Probabilistic Data Association. It was derived applying statistical inference techniques on a fully probabilistic model. In our proposal, each point in the source point cloud is associated with a set of points in the target point cloud; each association is then weighted so that the weights form a probability distribution. The result is an algorithm similar to ICP but more robust w.r.t. noise and outliers. While we designed our approach to deal with the problem of dense-sparse registration, it can be successfully applied also to standard point clouds registration.
Agamennoni, G., Fontana, S., Siegwart, R., & Sorrenti, D. (2016). Point Clouds Registration with Probabilistic Data Association. In IEEE International Conference on Intelligent Robots and Systems (pp.4092-4098). Institute of Electrical and Electronics Engineers Inc. [10.1109/IROS.2016.7759602].
Citazione: | Agamennoni, G., Fontana, S., Siegwart, R., & Sorrenti, D. (2016). Point Clouds Registration with Probabilistic Data Association. In IEEE International Conference on Intelligent Robots and Systems (pp.4092-4098). Institute of Electrical and Electronics Engineers Inc. [10.1109/IROS.2016.7759602]. | |
Tipo: | paper | |
Carattere della pubblicazione: | Scientifica | |
Presenza di un coautore afferente ad Istituzioni straniere: | Si | |
Titolo: | Point Clouds Registration with Probabilistic Data Association | |
Autori: | Agamennoni, G; Fontana, S; Siegwart, R; Sorrenti, D | |
Autori: | FONTANA, SIMONE (Primo) SORRENTI, DOMENICO GIORGIO (Ultimo) | |
Data di pubblicazione: | 2016 | |
Lingua: | English | |
Nome del convegno: | IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS October 9-14 | |
ISBN: | 9781509037629 | |
Serie: | PROCEEDINGS OF THE ... IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS | |
Digital Object Identifier (DOI): | http://dx.doi.org/10.1109/IROS.2016.7759602 | |
Appare nelle tipologie: | 02 - Intervento a convegno |
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