Browsing by Author "Wu, Chiao-Min"

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A Novel Sensory Mapping Design for Bipedal Walking on a Sloped Surface
(2012-10-12)
Wu, Chiao-Min
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Huang, Chao-Ping
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Hsieh, Chang-Hung
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Song, Kai-Tai
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電子工程學系及電子研究所
This paper presents an environment recognition method for bipedal robots using a time-delay neural network. For a robot to walk in a varying terrain, it is desirable that the robot can adapt to any environment encountered in real-time. This paper aims to develop a sensory mapping unit to recognize environment types from the input sensory data based on an artificial neural network approach. With the proposed sensory mapping design, a bipedal walking robot can obtain real-time environment information and select an appropriate walking pattern accordingly. Due to the time-dependent property of sensory data, the sensory mapping is realized by using a time-delay neural network. The sensory data of earlier time sequences combined with current sensory data are sent to the neural network. The proposed method has been implemented on the humanoid robot NAO for verification. Several interesting experiments were carried out to verify the effectiveness of the sensory mapping design. The mapping design is validated for the uphill, downhill and flat surface cases, where three types of environment can be recognized by the NAO robot online.
A Sensory Data Tracking Approach to Bipedal Gait Compensation Control on Slope Surfaces
(2013)
Wu, Chiao-Min
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Song, Kai-Tai
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電控工程研究所
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Institute of Electrical and Control Engineering
The development of biped robots has gained much research attention in recent years due to their capacity and flexibility in providing assistance to human. In practical applications, these robots are expected to walk on various types of ground surfaces. Balance control of bipedal walking on uneven terrain is still a challenging problem. This paper proposes a novel gait compensating method using sensory data tracking such that a robot can keep balance and walk on slope surfaces. The real-time compensation control system works to adjust the gait and thus make online sensory data to track the stored target sensory data, which are obtained from the robot when it walks on a flat surface. While the robot adjusts its gait to make online sensory data similar to those on a flat surface, it will achieve a stable pose in walking. The proposed method has been tested for several slopes using the NAO robot. The robot can adjust its pose automatically on slope surface according to the proposed method. An experiment on transition slopes further validates that the method can be extended to more general terrain variations for biped walking.