Several methods have been proposed in the literature to address the problem of automatic 3D reconstruction from depth data. Most methods rely on the minimization of the matching error among individual depth frames. However, ambiguity in sensor data often leads to erroneous matching (due to local minima), hard to cope with in a purely automatic approach. This paper proposes a semiautomatic approach, denoted interactive mapping, involving a human operator in the process of detecting and correcting erroneous matches. Instead of allowing the operator complete freedom in correcting the matching in a frame by frame basis, the proposed method constrains human intervention along the degrees of freedom with most uncertainty. This paper is targeted to 3D reconstruction from RGB-D data, such as the one provided by the Kinect sensor. The user is able to translate and rotate individual RGB-D point clouds, with the help of a force field-like reaction to the movement of each point cloud. Some preliminary results are presented, illustrating the advantages of the method.