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Article
ANN Control Based on Patterns Recognition for A Robotic Hand Under Different Load Conditions

Authors: Ihsan Abdulhussein Baqer --- Mauwafak Ali Tawfik --- Hayder Ahmed Abdulrazzaq
Journal: Journal of University of Babylon مجلة جامعة بابل ISSN: 19920652 23128135 Year: 2018 Volume: 26 Issue: 5 Pages: 176-198
Publisher: Babylon University جامعة بابل

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Abstract

In this paper, theArtificial Neural Network (ANN) istrained on the patterns of the normal component to tangential componentratios at the time of slippage occurrence, so that it can be able to distinguishthe slippage occurrence under different type of load (quasi-static and dynamic loads), and then generates a feedback signal used as an input signal to run the actuator. This process isexecuted without the need for any information about the characteristics of the grasped object, such as weight, surface texture, shape, coefficient of the friction and the type of the load exerted on the grasped object. For fulfillment this approach, a new fingertip design has been proposed in order to detect the slippage in multi-direction between the grasped object and the artificial fingertips. This design is composed of two under-actuated fingers with an actuation system which includes flexible parts (compressive springs). These springs operate as a compensator for the grasping force at the time of slippage occurrence in spite of the actuator is in stopped situation. The contact force component ratios can be calculated via a conventional sensor (Flexiforce sensor) after processed the force data using Matlab/Simulink program through a specific mathematical model which isderived according to the mechanism of the artificial finger.

في هذا البحث, الشبكة العصبية الاصطناعية (ANN) قد تم تدريبها على انماط نسب المركبات العمودية الى الافقية لقوى التماس عند وقت حدوث الانزلاق, لتكون قادرة على تمييز الانزلاق تحت انواع مختلفة من الأحمال (الحمل الستاتيكي والحمل الديناميكي), ومن ثم توليد اشارة راجعة تستخدم كمشغل لمحرك اليد الصناعية. هذه العملية اجريت بدون الحاجة لأي معلومات حول خواص الجسم الممسوك, مثل الوزن, تركيب السطح, الشكل, معامل الاحتكاك و نوعالحمل المؤثر على الجسم الممسوك. لتحقيق ذلك , تم اقتراح تصميم جديد لرأس الاصبع من اجل كشف الانزلاق في اتجاهات متعددة بين الجسم الممسوك ورؤس الاصابع الاصطناعية. هذا التصميم يتألف من اصبعين مع نظام تشغيل يتضمن اجزاء مرنة (نوابض انضغاطية). هذه النوابض تعمل كمعوض لقوة المسك عند وقت حدوث الانزلاق حتى في وضعية التوقف لمحرك اليد. نسب مركبات قوى التماس يمكن حسابها بواسطة حساسات قوى تقليدية (FlexiForce sensor) بعد معالجة بيانات القوى باستخدام برنامج Matlab/Simulinkومن خلال علاقات رياضية معينة التي تم اشتقاقهالوصف الآلية الميكانيكية للإصبع الاصطناعي.


Article
SLIP DETECTION FOR A SPECIFIC DESIGN OF FINGERTIP IN MULTI-DIRECTION UNDER DIFFERENT LOAD CONDITIONS

Authors: Hayder Ahmed Abdulrazzaq --- Ihsan Abdulhussein Baqer --- Mauwafak Ali Tawfik
Journal: Journal of Engineering and Sustainable Development مجلة الهندسة والتنمية المستدامة ISSN: 25200917 Year: 2019 Volume: 23 Issue: 1 Pages: 103-116
Publisher: Al-Mustansyriah University الجامعة المستنصرية

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Abstract

In this paper, a novel design of robotic fingertip has been proposed to detect slippage between the robotic fingertip and the grasped object in multi-direction under different types of loads (static and dynamic loads). The detection process is based on the monitoring of variation in the normal to the tangential component of contact force ratios. The fingertip is composed of a compression springs and a conventional force sensors that are mounted to be able to measure the contact force components continuously. A mathematical model has been derived relative to a proposed design with the help of Matlab-Simulink program. Furthermore, the robotic hand mechanism contains the flexible parts to adapt the grasping force during the slippage occurrence period in spite of the hand actuator is in a stopped status. The grasped object is designed in a cube shape with two unbalance DC motors to generate an excitation that is used as an external dynamic load. The experimental results revealed that the proposed design for detecting slippage in multi-direction is feasible and effective for improving the stability of the grasping process.

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