Pose Estimation of Construction Materials by Acquisition of Multiple IDs of Devices

Abstract

It is a crucial issue for building the relationship between states of the construction materials at the construction site and their information such as their existence, pose (pose and orientation), forms, task information for workers or robots, and so on, for efficient construction automation (Umetani et al., 2006). One of the methods for building the relationship is using ID devices, for example, radio frequency identification devices and barcodes (Want et al., 1999) (Penttila et al., 2004). Several studies using ID devices attached to the construction materials have been introduced, for example, tracking of the construction materials at the construction site (Akinchi et al., 2002) (Jaselskis et al., 1995) (Jaselskis & ElMisalami, 2003), tracking of the tools for the workers (Goodrum et al., 2006), and scheduling of the construction site including the production of the construction materials (Yagi et al., 2005). This chapter describes a method of the pose (position and orientation) of the construction materials using multiple ID devise to maintain the relationship between the status of the materials and their information. Object pose is important status for construction tasks; however, the object pose can be changed by the workers or robots that cannot update the data of the object. In this case, the workers and robots should measure the object pose. The proposed method estimates the object pose using at least two ID devices attached to the object. The chapter focuses on the simplification of the pose estimation and the geometrical condition of the ID devices using pose estimation. Several pose estimation method of the construction materials. Furlani has been proposed pose estimation using at least not aligned three RFID devices based on the device position with respect to the object coordination frame (Furlani & Stone, 1999). Umetani has been proposed pose estimation using at least two ID devices attached to the different sides of the object based on the device position and orientation with respect to the object coordination frame (Umetani et al., 2003). Former one is not considered to the motion planning of the ID reader because the method does not apply the orientation of the ID reader. On the other hand, the latter one uses the full orientation of the ID device. It is difficult to register the orientation of the ID devices. This chapter shows feasibility of the proposed method through the modeling result of the pose estimation and experimental results. The paper introduces integration of the objects