Biological robot arm motion through reinforcement learning

2003 ◽  
Author(s):  
J. Izawa ◽  
T. Kondo ◽  
K. Ito
Keyword(s):  
Reinforcement Learning ◽  
Robot Arm ◽  
Arm Motion

ROBOTIC HANDWRITING

2005 ◽  
Vol 02 (01) ◽  
pp. 105-124 ◽  
Author(s):  
VELJKO POTKONJAK
Keyword(s):  
Mathematical Models ◽  
Muscle Fatigue ◽  
Simulation Study ◽  
Robot Control ◽  
Robot Arm ◽  
Redundancy Resolution ◽  
Kinematic Redundancy ◽  
New Concepts ◽  
Human Arm ◽  
Arm Motion

Handwriting has always been considered an important human task, and accordingly it has attracted the attention of researchers working in biomechanics, physiology, and related fields. There exist a number of studies on this area. This paper considers the human–machine analogy and relates robots with handwriting. The work is two-fold: it improves the knowledge in biomechanics of handwriting, and introduces some new concepts in robot control. The idea is to find the biomechanical principles humans apply when resolving kinematic redundancy, express the principles by means of appropriate mathematical models, and then implement them in robots. This is a step forward in the generation of human-like motion of robots. Two approaches to redundancy resolution are described: (i) "Distributed Positioning" (DP) which is based on a model to represent arm motion in the absence of fatigue, and (ii) the "Robot Fatigue" approach, where robot movements similar to the movements of a human arm under muscle fatigue are generated. Both approaches are applied to a redundant anthropomorphic robot arm performing handwriting. The simulation study includes the issues of legibility and inclination of handwriting. The results demonstrate the suitability and effectiveness of both approaches.

Robot Trajectory Planning Using Rational Frenet-Serret Curves

Volume 2 ◽  
2004 ◽  
Author(s):  
Reza Ravani ◽  
Ali Meghdari
Keyword(s):  
Trajectory Planning ◽  
Computer Animation ◽  
Rational Curves ◽  
Robot Arm ◽  
Robot Trajectory ◽  
Arm Motion ◽  
Sweep Surface ◽  
And Robotics ◽  
Rotation Minimizing Frame ◽  
Robot Trajectory Planning

The aim of this paper is to demonstrate that the techniques of Computer Aided Geometric Design such as spatial rational curves and surfaces could be applied to Kinematics, Computer Animation and Robotics. For this purpose we represent a method which utilizes a special class of rational curves called Rational Frenet-Serret (RF) [8] curves for robot trajectory planning. RF curves distinguished by the property that the motion of their Frenet-Serret frame is rational. We describe an algorithm for interpolation of positions by a rational Frenet-Serret motion. Further more we provide an analysis on spatial frames (Frenet-Serret frame and Rotation Minimizing frame) for smooth robot arm motion and investigate their applications in sweep surface modeling.

EEG-Induced Autonomous Game-Teaching to a Robot Arm by Human Trainers Using Reinforcement Learning

2021 ◽  
pp. 1-1
Author(s):  
Reshma Kar ◽  
Lidia Ghosh ◽  
Amit Konar ◽  
Aruna Chakraborty ◽  
Atulya K. Nagar
Keyword(s):  
Reinforcement Learning ◽  
Robot Arm

A Model of Human Reaction Time to Dangerous Robot Arm Movements

1987 ◽  
Vol 31 (2) ◽  
pp. 191-195 ◽  
Author(s):  
Martin G. Helander ◽  
Mark H. Karwan ◽  
John Etherton
Keyword(s):  
Decision Making ◽  
Reaction Time ◽  
Motor Response ◽  
Arm Movements ◽  
Robot Arm ◽  
Total Reaction ◽  
Human Reaction ◽  
Arm Motion ◽  
Human Reaction Time ◽  
Total Reaction Time

An increasing number of studies indicate that robots are the most hazardous equipment in industry. The very virtue that makes them attractive for industrial work, the programmable arm, is the cause of accidents since the arm motion is often difficult to perceive. The present paper presents a model of human reaction time and emergency behavior. The total reaction time is the sum of three elements: perception, decision making and motor response. Each of these three elements are modeled using concepts such as perceptual discriminability and single detection theory. Finally the results of an experiment is presented where the human reaction time is modeled as a function of robot arm speed.

A Robot Arm Motion Generation Based on Learning of Objects Shape and Human Motion

2018 ◽  
Vol 2018 (0) ◽  
pp. 2A1-F14
Author(s):  
Sho TAJIMA ◽  
Tokuo TSUJI ◽  
Yosuke SUZUKI ◽  
Tetsuyou WATANABE ◽  
Kenichi MOROOKA ◽  
...  
Keyword(s):  
Human Motion ◽  
Robot Arm ◽  
Motion Generation ◽  
Arm Motion
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