Acoustic surface perception through the ground interaction of compliant legs of a hexapod robot

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Tezin Türü: Yüksek Lisans

Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Fen Bilimleri Enstitüsü, Türkiye

Tezin Onay Tarihi: 2012

Tezin Dili: İngilizce

Öğrenci: MİNE CÜNEYİTOĞLU ÖZKUL

Asıl Danışman (Eş Danışmanlı Tezler İçin): Yiğit Yazıcıoğlu

Eş Danışman: Afşar Saranlı

Özet:

A dynamically dexterous legged robot platform generates specific acoustic signals during the interaction with the ground and the environment. These acoustic signals are expected to contain rich information that is related to the interaction surface as a function of the position of the legs and the overall contact process mixed with the actuator sounds that initiate the movement. As the robot platform walks or runs in any environment, this convolved acoustic signal created can be processed and analyzed in real time operation and the interaction surface can be identified. Such an utilization of acoustic data can be possible for various indoor and outdoor surfaces and with this can be useful in adjusting gait parameters that play an essential role in dynamic dexterity. In this work, surface type identification is achieved with using the several popular signal processing and pattern classification methods not on the robot platform but off-line. The performances of the selected features and the algorithms are evaluated for the collected data sets and these outputs are compared with the expectations. Depending on the off-line training and experiment results, the applicability of the study to an embedded robot platform as a future application is found quite feasible and the surface type as an input to the robot sensing is expected to improve the mobility of the robot in both indoor and outdoor environment.