In-situ 3D Modeling becomes increasingly prominent in current Augmented Reality research, particularly for mobile scenarios. However, real-time performance and qualitative modeling remain highly challenging. In this work, we propose a new interactive 3D modeling approach for indoor environments, combining an assistive user interface and constrained reconstruction with a device consisting of a single-point laser range finder and a camera. Using our system, a user pans around capturing a panorama of the environment, while simultaneously measuring the distance to a single point per frame. An automatic detection process estimates planes from these sparse 3D measurements. The user can highlight specific geometric features in the environment, such as 2- or 3-way corners, with simple gestures, adding more 3D points to the estimation. The segmented planes are refined using a constrained optimization, enforcing orthogonality and parallel constraints as well as minimizing the number of planes used in the reconstruction. Finally a volumetric space-carving approach determines the geometry of the environment. Our reconstruction approach can output highly accurate models built only from simple, clean geometry. To examine the quantitative performance of our approach, we run evaluations on both synthetic and real data.