Browsing by Author "Lin, Chao-Yu"

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Mobile Manipulation and Visual Servoing Design of a Configurable Mobile Manipulator
(2013-01-01)
Song, Kai-Tai
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Jiang, Sin-Yi
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Wu, Ching-Jui
;
Lin, Ming-Han
;
Wu, Cheng Hei
This paper presents a mobile manipulation and visual servoing design for a configurable mobile manipulator by using a Kinect sensor. To achieve this goal, an image-based grasping design is combined with a visual simultaneous localization and mapping (vSLAM). The proposed vSLAM method is based on extended Kalman filter (EKF) and a Kinect RGBD sensor. In the manipulator design, the robot arms are designed to be able to configure as a handrail for user support in execution of walking assistance tasks. The purpose of this design is to perform mobile manipulation and walking assistance tasks on the same robot. Experiments on the prototype dual-arm mobile manipulator validate that the proposed method can find and grasp a target object after navigation a distance to the object position. After the robot delivered the object to the user, it configured to provide walking assist to the user using the suggested compliance controller.
Robust Facial Emotion Recognition Using a Temporal-Reinforced Approach
(2014)
Song, Kai-Tai
;
Lin, Chao-Yu
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電控工程研究所
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Institute of Electrical and Control Engineering
In this paper, a temporal-reinforced approach to enhancing emotion recognition from facial images is presented. Shape and texture models of facial images are computed by using active appearance model (AAM), from which facial feature points and geometrical feature values are extracted. The extracted features are used by relevance vector machine (RVM) to recognize emotional states. We propose a temporal analysis approach to recognizing likelihood of emotional categories, such that more subtle emotion, such as degree and ratio of basic emotional states can be obtained. Furthermore, a method is developed to map the recognition result to the arousal-valence plane (A-V Plane). Experimental results verify that the performance of emotion recognition is enhanced by the proposed method.
User Identification Design by Fusion of Face Recognition and Speaker Recognition
(2012-01-01)
Lin, Chao-Yu
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Song, Kai-Tai
;
Chen, Yi-Wen
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Chien, Shuo-Cheng
;
Chen, Sin-Horng
Intelligent human-robot interface helps a mobile robot to extract external information and interact with a user. User identification information allows a robot to generate appropriate behaviors and make personalized human-robot interaction (PHRI) more natural and safe. Most of service robots move around in various application settings, and biometric features always change during relative movements. In this work, a fusion recognition system based on face and speaker classifiers is designed to achieve the user recognition in various environments. We propose a method to fuse face and speech recognition results based on the concept of confidence indices. Through the derived confidence indices, the system combines the two classifiers and gives improved recognition results. Experiments on a laboratory home service robot show that person recognition rates in 15 environmental situations all outperform those of using single modality.