Real-time 3D visual sensor for robust object recognition.
ABSTRACT This paper presents a novel 3D measurement system, which yields both depth and color information in real time, by calibrating a time-of-flight and two CCD cameras. The problem of occlusions is solved by the proposed fast occluded-pixel detection algorithm. Since the system uses two CCD cameras, missing color information of occluded pixels is covered by one another. We also propose a robust object recognition using the 3D visual sensor. Multiple cues, such as color, texture and 3D (depth) information, are integrated in order to recognize various types of objects under varying lighting conditions. We have implemented the system on our autonomous robot and made the robot do recognition tasks (object learning, detection, and recognition) in various environments. The results revealed that the proposed recognition system provides far better performance than the previous system that is based only on color and texture information.
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ABSTRACT: In this paper, we propose a robot that acquires multimodal information, i.e. visual, auditory, and haptic information, fully autonomously using its embodiment. We also propose batch and online algorithms for multimodal categorization based on the acquired multimodal information and partial words given by human users. To obtain multimodal information, the robot detects an object on a flat surface. Then, the robot grasps and shakes it to obtain haptic and auditory information. For obtaining visual information, the robot uses a small hand-held observation table with an XBee wireless controller to control the viewpoints for observing the object. In this paper, for multimodal concept formation, multimodal latent Dirichlet allocation using Gibbs sampling is extended to an online version. This framework makes it possible for the robot to learn object concepts naturally in everyday operation in conjunction with a small amount of linguistic information from human users. The proposed algorithms are implemented on a real robot and tested using real everyday objects to show the validity of the proposed system.Advanced Robotics 12/2012; 26(17). DOI:10.1080/01691864.2012.728693 · 0.56 Impact Factor
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ABSTRACT: In this study, we propose a system to enable robots to navigate more efficiently to target objects in order to carry out mobile manipulation tasks. Because a robot arm has limited reach, a target object cannot be grasped if the distance to the object exceeds the reach. At the same time, navigation errors may increase as the robot moves around in an environment. To mitigate these problems, we propose the use of maps that express the arm reachability and navigation reachability. Places with minimum probability of navigation errors and maximum tolerable navigation errors for the reach of the arm can be determined by integrating these two maps. We also consider the fact that the target object position is not always known. To cope with this problem, we introduce an object existence map that represents the ambiguity of the target object position, considering the past position. If the ambiguity is large, it is possible to select a place from where the object searching task can be performed with a wide angle of view by the robot. Efficient object searching can be achieved by changing the task objective from searching to grasping and vice versa. We conducted some mobile manipulation tasks to evaluate the proposed method. The results showed that the proposed system can perform such tasks effectively.Intelligent Robots and Systems (IROS), 2012 IEEE/RSJ International Conference on; 01/2012
Conference Paper: Playmate robots that can act according to a child's mental state[Show abstract] [Hide abstract]
ABSTRACT: We propose a playmate robot system that can play with a child. Unlike many therapeutic service robots, our proposed playmate system is implemented as a functionality of the domestic service robot with a high degree of freedom. This implies that the robot can play high-level games with children, i.e., beyond therapeutic play, using its physical features. The proposed system currently consists of ten play modules, including a chatbot with eye contact, card playing, and drawing. The algorithms of these modules are briefly discussed in this paper. To sustain the player's interest in the system, we also propose an action-selection strategy based on a transition model of the child's mental state. The robot can estimate the child's state and select an appropriate action in the course of play. A portion of the proposed algorithms was implemented on a real robot platform, and experiments were carried out to design and evaluate the proposed system.Intelligent Robots and Systems (IROS), 2012 IEEE/RSJ International Conference on; 01/2012