Self-Calibration of Eye-to-Hand and Workspace for Mobile Service Robot

Self-Calibration of Eye-to-Hand and Workspace for Mobile Service Robot

Jwu-Sheng Hu (National Chiao Tung University, Taiwan & Industrial Technology Research Institute, Taiwan) and Yung-Jung Chang (National Chiao Tung University, Taiwan & Industrial Technology Research Institute, Taiwan)
Copyright: © 2014 |Pages: 18
DOI: 10.4018/978-1-4666-4607-0.ch072
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The geometrical relationships among robot arm, camera, and workspace are important to carry out visual servo tasks. For industrial robots, the relationships are usually fixed and well calibrated by experienced operators. However, for service robots, particularly in mobile applications, the relationships might be changed. For example, when a mobile robot attempts to use the visual information from environmental cameras to perform grasping, it is necessary to know the relationships before taking actions. Moreover, the calibration should be done automatically. This chapter proposes a self-calibration method using a laser distance sensor mounted on the robot arm. The advantage of the method, as compared with pattern-based one, is that the workspace coordinate is also obtained at the same time using the projected laser spot. Further, it is not necessary for the robot arm to enter the view scope of the camera for calibration. This increases the safety when the workspace is unknown initially.
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Distributed Vision System (DVS), a particular example of sensor network, consists of physical vision agents monitoring the working environment (Ishiguro, 1997). The vision agents connect with each other through computer network or are controlled by central computer. The concept of distributed vision system can be applied to construct a wide area surveillance system for human tracking (Atsushi et al., 1998; 2002), a robot indoor navigation system (Ishiguro, 1997; Nakazawa, et al., 1998; Sogo, et al., 1999), or a non-specific target tracking system (Takashi & Norimichi, 2002).

Positioning in three-dimensional space is an important technical issue in many industrial and commercial applications. Specifically, noncontact measurement of the rough surface of a target is useful in many industrial occasions because it is convenient and non-destructive. Distance measurement device based on laser diode technology can provide precise measurements. This kind of measurement device is called laser distance sensor or laser range finder. Laser distance measuring method can be technically divided into three categories: interferometry, time-of-flight, and triangulation and each of them have advantages and limitations (Amann, et al., 2001). A robot arm equipped with a 2-D laser range finder can take dimensional information of the target while adapting its view in applications such as 3-D scanning (Soucy, et al., 1998; Lamb, et al., 1999). In some applications where target locations (points) in space relative to the robot arm are required, it is sufficient to use a 1-D distance sensor mounted on the end effector. Usually a 1-D laser distance sensor with a visible laser light is able to serve the measurement purpose. In such a sensing system, the factors causing the systematic errors include imperfect position and orientation arguments of the laser distance sensor. Since the accuracy of such measurement system is influenced by the precision of installation parameters, the calibration is essential and critical.

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