An autonomous six-DOF eye-in-hand system for in situ 3D object modeling

Abstract

We present an integrated and fully autonomous eye-in-hand system for 3D object modeling. The system hardware consists of a laser range scanner mounted on a six-DOF manipulator arm and the task is to autonomously build a 3D model of an object in situ where the object may not be moved and must be scanned in its original location. Our system assumes no knowledge of object shape or geometry other than that it is within a bounding box whose location and size are known a priori, and, furthermore, the environment is unknown. The overall planner integrates the three main algorithms in the system: one that finds the next best view (NBV) for modeling the object; one that finds the NBV for exploration, i.e. exploring the environment, so the arm can move to the modeling view pose; and finally a sensor-based path planner, that is able to find a collision-free path to the view configuration determined by either of the the two view planners. Our modeling NBV algorithm efficiently searches the five-dimensional view space to determine the best modeling viewpoint, while considering key constraints such as field of view (FOV), overlap, and occlusion. If the determined viewpoint is reachable, the sensor-based path planner determines a collision-free path to move the manipulator to the desired view configuration, and a scan of the object is taken. Since the workspace is initially unknown, in some phases, the exploration view planner is used to increase information about the reachability and also the status of the modeling view configurations, since the view configuration may lie in an unknown workspace. This is repeated until the object modeling is complete or the planner deems that no further progress can be made, and the system stops. We have implemented the system with a six-DOF powercube arm and a wrist mounted Hokuyo URG-04LX laser scanner. Our results show that the system is able to autonomously build a 3D model of an object in situ in an unknown environment.

Keywords

Path planning for manipulators range sensing

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