A developmental grasp learning scheme for humanoid robots


Tezin Türü: Yüksek Lisans

Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü, Türkiye

Tezin Onay Tarihi: 2012

Öğrenci: ASİL KAAN BOZCUOĞLU

Danışman: EROL ŞAHİN

Özet:

While an infant is learning to grasp, there are two key processes that she uses for leading a successful development. In the first process, infants use an intuitional approach where the hand is moved towards the object to create an initial contact regardless of the object properties. The contact is followed by a tactile grasping phase where the object is enclosed by the hand. This intuitive grasping behavior leads an grasping mechanism, which utilizes visual input and incorporates this into the grasp plan. The second process is called scaffolding, a guidance by stating how to accomplish the task or modifying its behaviors by interference. Infants pay attention to such guidance and understand the indication of important features of an object from 9 months of age. This supervision mechanism plays an important role for learning how to grasp certain objects in a proper way. To simulate these behavioral findings, a reaching and a tactile grasping controller was implemented on iCub humanoid robot which allowed it to reach an object from different directions, and enclose its fingers to cover the object. With these, a human-like grasp learning for iCub is proposed. Namely, the first step is an unsupervised learning where the robot is experimenting how to grasp objects. The second step is supervised learning phase where a caregiver modifies the end-effectors position when the robot is mistaken. By doing several experiments for two different grasping styles, we observe that the proposed methodology shows a better learning rate comparing to the scaffolding-only learning mechanism.