Abstract
In this paper, a new object tracking system is proposed to improve the object manipulation capabilities of service robots. The goal is to continuously track the state of the visualized environment in order to send visual information in real time to the path planning and decision modules of the robot; that is, to adapt the movement of the robotic system according to the state variations appearing in the imaged scene. The tracking approach is based on a probabilistic collaborative tracking framework developed around a 2D patch-based tracking system and a 2D-3D point features tracker. The real-time visual information is composed of RGB-D data streams acquired from state-of-the-art structured light sensors. For performance evaluation, the accuracy of the developed tracker is compared to a traditional marker-based tracking system which delivers 3D information with respect to the position of the marker.
Highlights
One of the main tasks of service robotics systems operating in human environments, such as the FRIEND (Functional Robot with dexterous arm and user‐frIENdly interface for Disabled people) [1] and PR2 (Personal Robot 2) [2] platforms displayed in Figure 1, is to reliably handle common household objects, such as plates, bottles or boxes, usually placed in heavy cluttered scenes
There are a large number of image‐based trackers which accurately deliver visual information in the 2D image domain, the tracker presented in this paper is intended to be used in service robotics application where 3D information regarding the objects of interest is imperative
As a single hand‐held RGB‐D camera passes over a static scene, detailed textured depth maps at selected keyframes are estimated in order to produce a surface patchwork with millions of vertices
Summary
One of the main tasks of service robotics systems operating in human environments, such as the FRIEND (Functional Robot with dexterous arm and user‐frIENdly interface for Disabled people) [1] and PR2 (Personal Robot 2) [2] platforms displayed in Figure 1, is to reliably handle common household objects, such as plates, bottles or boxes, usually placed in heavy cluttered scenes. The main goal of tracking rigid bodies in robotics is to determine their pose with respect to a common reference coordinate system , such that, if the state of the environment changes, the manipulation path of the robotic system is changed . This challenge is illustrated, where different tracking snapshots of an object of interest are illustrated. The main advantage of such sensors is the calculated depth map, or point cloud, structure, which, along with the RGB image, describes the colour and real‐world distances between the sensor and the visualized surfaces They have become an intensively used perception sensor in a large number of indoor robotic applications. There are a large number of image‐based trackers which accurately deliver visual information in the 2D image domain, the tracker presented in this paper is intended to be used in service robotics application where 3D information regarding the objects of interest is imperative
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