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

scholarly journals Energy and Path Optimization of Robot Arm Simulator Via Multi-Objective Evolutionary Algorithm

2018 ◽  
Vol 7 (4.36) ◽  
pp. 404
Author(s):  
Z. Mohamed ◽  
N. S. Khusaini ◽  
M. A.M Anuar ◽  
R. Ramly ◽  
M. A Anuar ◽  
...  
Keyword(s):  
Minimum Distance ◽  
Minimum Energy ◽  
Path Optimization ◽  
Intelligent Robot ◽  
Robot Arm ◽  
Motion Generation ◽  
Neural Controller ◽  
New Approach ◽  
Neural Controllers ◽  
Arm Motion

The performance of robot arm motion generated via neural network are presented in this paper. The robot arm motion for obstacle avoidance simultaneously optimizing three functions; minimum distance, minimum time and minimum energy are generated. Four different initial and goal position had been chosen to test and analyze the performance of generated neural controller. The same neural controllers can be employed to a different range of initial and goal position. The motion generated yield good results in the simulator. In this research a new approach for intelligent robot arm path and motion generation are successfully implemented. 

Adaptive arm motion generation of humanoid robot operating in dynamic environments

2014 ◽  
Vol 41 (2) ◽  
pp. 124-134 ◽  
Author(s):  
Zulkifli Mohamed ◽  
Mitsuki Kitani ◽  
Genci Capi
Keyword(s):  
Humanoid Robot ◽  
Dynamic Environments ◽  
Robot Motion ◽  
Robot Arm ◽  
Objective Functions ◽  
Motion Generation ◽  
Content Type ◽  
Neural Controllers ◽  
Wide Range ◽  
Arm Motion

Purpose – The purpose of this paper is to compare the performance of the robot arm motion generated by neural controllers in simulated and real robot experiments. Design/methodology/approach – The arm motion generation is formulated as an optimization problem. The neural controllers generate the robot arm motion in dynamic environments optimizing three different objective functions; minimum execution time, minimum distance and minimum acceleration. In addition, the robot motion generation in the presence of obstacles is also considered. Findings – The robot is able to adapt its arm motion generation based on the specific task, reaching the goal position in simulated and experimental tests. The same neural controller can be employed to generate the robot motion for a wide range of initial and goal positions. Research limitations/implications – The motion generated yield good results in both simulation and experimental environments. Practical implications – The robot motion is generated based on three different objective functions that are simultaneously optimized. Therefore, the humanoid robot can perform a wide range of tasks in real-life environments, by selecting the appropriate motion. Originality/value – A new method for adaptive arm motion generation of a mobile humanoid robot operating in dynamic human and industrial environments.

An Efficient Motion Generation Method for Redundant Humanoid Robot Arm Based on the Intrinsic Principles of Human Arm Motion

2018 ◽  
Vol 15 (06) ◽  
pp. 1850026 ◽  
Author(s):  
Meng Li ◽  
Weizhong Guo ◽  
Rongfu Lin ◽  
Changzheng Wu ◽  
Liangliang Han
Keyword(s):  
Muscle Strength ◽  
Humanoid Robot ◽  
Computing Time ◽  
Strength Properties ◽  
Robotic Arm ◽  
Robot Arm ◽  
Kinematic Redundancy ◽  
Motion Generation ◽  
Human Arm ◽  
Arm Motion

The aim of this paper is trying to propose an efficient method of inverse kinematics and motion generation for redundant humanoid robot arm based on the intrinsic principles of human arm motion. The intrinsic principle analysis takes into account both the skeletal kinematics and muscle strength properties. Firstly, this work analyzed the kinematic redundancy problem of a human arm. By analyzing the biological feature of a human arm, the kinematic redundancy boils down to the uncertainty of elbow position. Secondly, because the muscle’s kinematic and strength properties are critical for simulating biometric motion authentically, the muscle strength property was introduced as the criterion for configuration identification and motion generation. Three types of limb configuration, dog walking, gecko climbing, and human walking limb configuration were analyzed, and two geometrical configuration identification rules were deduced to generate biomimetic motion for humanoid robotic arms. By comparing the proposed method with other five IK methods, the proposed method significantly deduced the computing time. Finally, the configuration identification rules were used to generate motions for a 7-DoF humanoid robotic arm. The results showed that the biological rules can generate biomimetic, smooth arm motions for a redundant humanoid robotic arm.

Assistive Humanoid Robot Arm Motion Generation in Dynamic Environment Based on Neural Networks

2015 ◽  
Vol 3 (2) ◽  
pp. 115-121
Author(s):  
Genci Capi ◽  
Zulkifli Mohamed ◽  
Mitsuki Kitani ◽  
Shin-ichiro Kaneko
Keyword(s):  
Neural Networks ◽  
Humanoid Robot ◽  
Dynamic Environment ◽  
Robot Arm ◽  
Motion Generation ◽  
Arm Motion

scholarly journals Intuitive Kinematic Control of a Robot Arm via Human Motion

2014 ◽  
Vol 79 ◽  
pp. 411-416 ◽  
Author(s):  
Hsien-I Lin ◽  
Yu-Cheng Liu ◽  
Yu-Hsiang Lin
Keyword(s):  
Human Motion ◽  
Robot Arm ◽  
Kinematic Control

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.

Robot Arm Motion Planning Based on Geodesics

2021 ◽  
Author(s):  
Mario Laux ◽  
Andreas Zell
Keyword(s):  
Motion Planning ◽  
Robot Arm ◽  
Arm Motion
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