%0 Journal Article %1 Pomerleau:2015:RPC:2802190.2802191 %A Pomerleau, Francois %A Colas, Francis %A Siegwart, Roland %C Hanover, MA, USA %D 2015 %I Now Publishers Inc. %J Found. Trends Robot %K 2015 algorithms book correspondence mobile point-cloud %N 1 %P 1--104 %R 10.1561/2300000035 %T A Review of Point Cloud Registration Algorithms for Mobile Robotics %U http://dx.doi.org/10.1561/2300000035 %V 4 %X The topic of this review is geometric registration in robotics. Registrationalgorithms associate sets of data into a common coordinate system.They have been used extensively in object reconstruction, inspection,medical application, and localization of mobile robotics. We focus onmobile robotics applications in which point clouds are to be registered.While the underlying principle of those algorithms is simple, manyvariations have been proposed for many different applications. In thisreview, we give a historical perspective of the registration problem andshow that the plethora of solutions can be organized and differentiatedaccording to a few elements. Accordingly, we present a formalizationof geometric registration and cast algorithms proposed in the literatureinto this framework. Finally, we review a few applications of thisframework in mobile robotics that cover different kinds of platforms,environments, and tasks. These examples allow us to study the specificrequirements of each use case and the necessary configuration choicesleading to the registration implementation. Ultimately, the objective ofthis review is to provide guidelines for the choice of geometric registrationconfiguration.

@article{Pomerleau:2015:RPC:2802190.2802191, abstract = {The topic of this review is geometric registration in robotics. Registrationalgorithms associate sets of data into a common coordinate system.They have been used extensively in object reconstruction, inspection,medical application, and localization of mobile robotics. We focus onmobile robotics applications in which point clouds are to be registered.While the underlying principle of those algorithms is simple, manyvariations have been proposed for many different applications. In thisreview, we give a historical perspective of the registration problem andshow that the plethora of solutions can be organized and differentiatedaccording to a few elements. Accordingly, we present a formalizationof geometric registration and cast algorithms proposed in the literatureinto this framework. Finally, we review a few applications of thisframework in mobile robotics that cover different kinds of platforms,environments, and tasks. These examples allow us to study the specificrequirements of each use case and the necessary configuration choicesleading to the registration implementation. Ultimately, the objective ofthis review is to provide guidelines for the choice of geometric registrationconfiguration.}, acmid = {2802191}, added-at = {2018-04-28T19:20:31.000+0200}, address = {Hanover, MA, USA}, author = {Pomerleau, Fran\c{c}ois and Colas, Francis and Siegwart, Roland}, biburl = {https://www.bibsonomy.org/bibtex/227b1e84fe367792aab49dd5011c31684/achakraborty}, description = {A Review of Point Cloud Registration Algorithms for Mobile Robotics}, doi = {10.1561/2300000035}, interhash = {d5d99b8b96ef527b81e30b3487841c6b}, intrahash = {27b1e84fe367792aab49dd5011c31684}, issn = {1935-8253}, issue_date = {05 2015}, journal = {Found. Trends Robot}, keywords = {2015 algorithms book correspondence mobile point-cloud}, month = may, number = 1, numpages = {104}, pages = {1--104}, publisher = {Now Publishers Inc.}, timestamp = {2018-04-28T19:20:31.000+0200}, title = {A Review of Point Cloud Registration Algorithms for Mobile Robotics}, url = {http://dx.doi.org/10.1561/2300000035}, volume = 4, year = 2015 }