Distinguish the textures of grasped objects by robotic hand using artificial neural-network
المؤلفون المشاركون
Muhsin, Hamzah N.
Salman, Hasan D.
Bakhy, Sadiq Husayn
المصدر
Engineering and Technology Journal
العدد
المجلد 39، العدد 9 (30 سبتمبر/أيلول 2021)، ص ص. 1420-1429، 10ص.
الناشر
تاريخ النشر
2021-09-30
دولة النشر
العراق
عدد الصفحات
10
التخصصات الرئيسية
الموضوعات
الملخص EN
The object identification properties with tactile sensing are valuable in interaction with the environment for both humans and robots, and it is the core of sensing used for exploration and determining properties of objects that are inaccessible from visual perception.
Object identification often involves with rigid mechanical grippers, tactile information and intelligent algorithms.
This paper proposes a methodology for feature extraction techniques and discriminates objects for different softness using adaptive robotic grippers, which are equipped with force and angle sensors in each four fingers of an underactuated robot hand.
Arduino microcontroller and the Matlab program are integrated to acquire sensor data and to control the gripping action.
The neural-network method used as an intelligent classifier to distinguish between different object softness by using feature vector acquired from the force sensor measurements and actuator positions in time series response during the grasping process using only a single closure grasping.
The proposed method efficiency was validated using experimental paradigms that involving three sets of model objects and everyday life objects with various shapes, stiffness, and The object identification properties with tactile sensing are valuable in interaction with the environment for both humans and robots, and it is the core of sensing used for exploration and determining properties of objects that are inaccessible from visual perception.
Object identification often involves with rigid mechanical grippers, tactile information and intelligent algorithms.
This paper proposes a methodology for feature extraction techniques and discriminates objects for different softness using adaptive robotic grippers, which are equipped with force and angle sensors in each four fingers of an underactuated robot hand.
Arduino microcontroller and the Matlab program are integrated to acquire sensor data and to control the gripping action.
The neural-network method used as an intelligent classifier to distinguish between different object softness by using feature vector acquired from the force sensor measurements and actuator positions in time series response during the grasping process using only a single closure grasping.
The proposed method efficiency was validated using experimental paradigms that involving three sets of model objects and everyday life objects with various shapes, stiffness, and sizes.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Salman, Hasan D.& Muhsin, Hamzah N.& Bakhy, Sadiq Husayn. 2021. Distinguish the textures of grasped objects by robotic hand using artificial neural-network. Engineering and Technology Journal،Vol. 39, no. 9, pp.1420-1429.
https://search.emarefa.net/detail/BIM-1281521
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Bakhy, Sadiq Husayn…[et al.]. Distinguish the textures of grasped objects by robotic hand using artificial neural-network. Engineering and Technology Journal Vol. 39, no. 9 (2021), pp.1420-1429.
https://search.emarefa.net/detail/BIM-1281521
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Salman, Hasan D.& Muhsin, Hamzah N.& Bakhy, Sadiq Husayn. Distinguish the textures of grasped objects by robotic hand using artificial neural-network. Engineering and Technology Journal. 2021. Vol. 39, no. 9, pp.1420-1429.
https://search.emarefa.net/detail/BIM-1281521
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references : p. 1428-1429
رقم السجل
BIM-1281521
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر