Browsing by Author "Cheng, Chieh- Cheng"

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Gaussian mixture-sound field landmark model for robot localization
(2005)
Wu, Li-Wei
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Cheng, Chieh- Cheng
;
Liu, Wei-Han
;
Hu, Jwu-Sheng
;
電控工程研究所
This investigation proposes a robust robot localization system. The system contains a novel Gaussian Mixture-Sound Field Landmark Model (GM-SFLM) and can localize the robot accurately in noisy environments. Moreover, the proposed method depends nothing on the geometry relation between source locations and two microphones; it is able to cover both near-field and far-field problems. With this proposed GM-SFLM, we can localize robot in 2-dimentional indoor environments. Furthermore, we realize the GM-SFLM into a quadruped robot system composed of an eRobot and a robot agent by using embedded Ethernet technology. The experiment demonstrates that when the robot is completely non-line-of-sight, this system still provides high detection accuracy. Additionally, the proposed method has advantages of high accuracy, low-cost, easy to implement and environmental adaptation.
Speaker attention system for mobile robots using microphone array and face tracking
(2006)
Song, Kai-Tai
;
Hu, Jwu-Sheng
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Tsai, Chi-Yi
;
Chou, Chung-Min
;
Cheng, Chieh- Cheng
This paper presents a real-time human-robot interface system (HRIS), which processes both speech and vision information to improve the quality of communication between human and an autonomous mobile robot. The HRIS contains a real-time speech attention system and a real-time face tracking system. In the speech attention system, a microphone-array voice acquisition system has been developed to estimate the direction of speaker and purify the speaker's speech signal in a noisy environment. The developed face tracking system aims to track the speaker's face under illumination variation and react to the face motion. The proposed HRIS can provide a robot with the abilities of finding a speaker's direction, tracking the speaker's face, moving its body to the speaker, focusing its attention to the speaker who is talking to it, and purifying the speaker's speech. The experimental results show that the HRIS not only purifies speech signal with a significant performance, but also tracks a face under illumination variation in real-time.