The production of a Building Information Model (BIM) from an existing asset is currently expensive and needs automation of the registration of the different acquisition data, including the registration of indoor and outdoor data. This kind of registration is considered a challenging problem, especially when both data sets are acquired separately and use different types of sensors. Besides, comparing a BIM to as-built data is an important factor to perform building progress monitoring and quality control. To carry out this comparison, the data sets must be registered. In order to solve both registration problems, we introduce two efficient algorithms. The first offers a potential solution for indoor/outdoor registration based on heterogeneous features (openings and planes). The second is based on linear features and proposes a potential solution for LiDAR data/BIM model registration. The common point between the approaches consists in the definition of a global robust distance between two segment sets and the minimization of this distance based on the RANSAC paradigm, finding the rigid geometric transformation that is the most consistent with all the information in the data sets.