Mapping and determining the center of mass of a rotating object using a moving observer

• Main Authors: Setterfield, Timothy Philip (Contributor), Miller, David W (Contributor), Leonard, John J (Contributor), Saenz Otero, Alvar (Contributor)
• Other Authors: Massachusetts Institute of Technology. Department of Aeronautics and Astronautics (Contributor), Massachusetts Institute of Technology. Department of Mechanical Engineering (Contributor), Massachusetts Institute of Technology. Department of Ocean Engineering (Contributor)
• Format: Article
• Language: English
• Published: SAGE Publications, 2018-02-16T18:13:00Z.
• Subjects: Article
• Online Access: Get fulltext

For certain applications, such as on-orbit inspection of orbital debris, defunct satellites, and natural objects, it is necessary to obtain a map of a rotating object from a moving observer, as well to estimate the object's center of mass. This paper addresses these tasks using an observer that measures its own orientation, angular rate, and acceleration, and is equipped with a dense 3D visual sensor, such as a stereo camera or a light detection and ranging (LiDAR) sensor. The observer's trajectory is estimated independently of the target object's rotational motion. Pose-graph mapping is performed using visual odometry to estimate the observer's trajectory in an arbitrary target-fixed frame. In addition to applying pose constraint factors between successive frames, loop closure is performed between temporally non-adjacent frames. A kinematic constraint on the target-fixed frame, resulting from the rigidity of the target object, is exploited to create a novel rotation kinematic factor. This factor connects a trajectory estimation factor graph with the mapping pose graph, and facilitates estimation of the target's center of mass. Map creation is performed by transforming detected feature points into the target-fixed frame, centered at the estimated center of mass. Analysis of the algorithm's computational performance reveals that its computational cost is negligible compared with that of the requisite image processing. Keywords: SLAM; dynamic; rotation kinematic factor
United States. Defense Advanced Research Projects Agency (Grant NNH11CC25C)
United States. Defense Advanced Research Projects Agency (Grant NNH13CJ23C)