Robot Arm Control Using Reward-Modulated Hebbian Learning

2021 ◽  
pp. 55-63
Author(s):  
Koutaro Minato ◽  
Yuichi Katori
Keyword(s):  
Hebbian Learning ◽  
Robot Arm ◽  
Robot Arm Control

scholarly journals Hebbian learning for online prediction, neural recall and classical conditioning of anthropomimetic robot arm motions

2018 ◽  
Vol 13 (6) ◽  
pp. 066009
Author(s):  
Benedikt Feldotto ◽  
Florian Walter ◽  
Florian Röhrbein ◽  
Alois Knoll
Keyword(s):  
Classical Conditioning ◽  
Hebbian Learning ◽  
Robot Arm ◽  
Arm Motions ◽  
Online Prediction

Development of the Robot Arm Control System Using Forearm SEMG

2009 ◽  
pp. 710-713
Author(s):  
Yusuke Wakita ◽  
Noboru Takizawa ◽  
Kentaro Nagata ◽  
Kazushige Magatani
Keyword(s):  
Control System ◽  
Robot Arm ◽  
Robot Arm Control

scholarly journals Tactile Slippage Analysis in Optical Three-Axis Tactile Sensor for Robotic Hand

2013 ◽  
Vol 465-466 ◽  
pp. 1375-1379
Author(s):  
Hanafiah Yussof ◽  
Zahari Nur Ismarrubie ◽  
Ahmad Khushairy Makhtar ◽  
Masahiro Ohka ◽  
Siti Nora Basir
Keyword(s):  
Control Algorithm ◽  
Tactile Sensor ◽  
Robotic Hand ◽  
Robot Hand ◽  
Robot Arm ◽  
Tactile Sensors ◽  
Shear Forces ◽  
Improve Performance ◽  
Robot Arm Control ◽  
Two Phases

This paper presents experimental results of object handling motions to evaluate tactile slippage sensation in a multi fingered robot arm with optical three-axis tactile sensors installed on its two hands. The optical three-axis tactile sensor is a type of tactile sensor capable of defining normal and shear forces simultaneously. Shear force distribution is used to define slippage sensation in the robot hand system. Based on tactile slippage analysis, a new control algorithm was proposed. To improve performance during object handling motions, analysis of slippage direction is conducted. The control algorithm is classified into two phases: grasp-move-release and grasp-twist motions. Detailed explanations of the control algorithm based on the existing robot arm control system are presented. The experiment is conducted using a bottle cap, and the results reveal good performance of the proposed control algorithm to accomplish the proposed object handling motions.

Robot Arm Control by Selectively Generated EMG

1993 ◽  
Vol 5 (3) ◽  
pp. 302-305
Author(s):  
Yoshiyuki Kageyama ◽  
◽  
Kiyoyuki Yamazaki ◽  
Kiyotaka Hoshiai
Keyword(s):  
Robot Arm ◽  
Robot Arm Control

3P2-V03 Robot arm control using Kinect(Non-contact Sensing)

2014 ◽  
Vol 2014 (0) ◽  
pp. _3P2-V03_1-_3P2-V03_2
Author(s):  
Kouhei ICHIMURA ◽  
Kazushige MAGATANI
Keyword(s):  
Robot Arm ◽  
Robot Arm Control ◽  
Contact Sensing
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