Probabilistic Modeling of Human Locomotion for Biped Robot Trajectory Generation

Author(s):  
Bharat Singh ◽  
Vishu Gupta ◽  
Rajesh Kumar
2013 ◽  
Vol 816-817 ◽  
pp. 712-716
Author(s):  
Ahmad Ghanbari ◽  
S. Mohammad Reza S. Noorani ◽  
Hamid HajiMohammadi ◽  
Aida Parvaresh

Naturalistic walking is one of the most important purposes of researches on biped robots. A feasible way is to translate the understanding of human walking to robot walking. One of the options that affects the quality of motion in a biped robot is concerned with trajectory generation. So, in this paper it's focused on trajectory generation methods for implementing a 7-links planar walker biped robot. Also, this model is simulated by VisualNastran software package and run according to a Clinical Gait Analysis (CGA) reference that has been modified for a planar model. Lastly, the results of simulation are reported.


2010 ◽  
Vol 8 (2) ◽  
pp. 339-351 ◽  
Author(s):  
Chan-Soo Park ◽  
Taesin Ha ◽  
Joohyung Kim ◽  
Chong-Ho Choi

2010 ◽  
Vol 108-111 ◽  
pp. 1439-1445
Author(s):  
Shahed Shojaeipour ◽  
Sallehuddin Mohamed Haris ◽  
Ehsan Eftekhari ◽  
Ali Shojaeipour ◽  
Ronak Daghigh

In this article, the development of an autonomous robot trajectory generation system based on a single eye-in-hand webcam, where the workspace map is not known a priori, is described. The system makes use of image processing methods to identify locations of obstacles within the workspace and the Quadtree Decomposition algorithm to generate collision free paths. The shortest path is then automatically chosen as the path to be traversed by the robot end-effector. The method was implemented using MATLAB running on a PC and tested on a two-link SCARA robotic arm. The tests were successful and indicate that the method could be feasibly implemented on many practical applications.


2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Zhaoming Liu ◽  
Nailong Liu ◽  
Hongwei Wang ◽  
Shen Tian ◽  
Ning Bai ◽  
...  

Motion modularity is the main method of motion control for higher animals. That means the complex movements of the muscles are made up of basic motion primitives, and the brain or central nervous system does not care about the specific details of the movement. However, the industrial robot control system does not adopt the technical roadmap of motion modularity, it generates complex trajectories by providing a large number of sampling points. This approach is equivalent to using the brain to directly guide the specific movement of the muscle and has to rely on a faster Fieldbus system to obtain complex motion trajectories. This work constructs a modularized industrial robot trajectory generation component based on Dynamic Movement Primitives (DMP) theory. With this component, the robot controller can generate complex trajectories without increasing the sampling points and can obtain good trajectory accuracy. Finally, the rationality of this system is proved by simulations and experiments.


2016 ◽  
Vol 13 (2) ◽  
pp. 271-282 ◽  
Author(s):  
Hongbo Zhu ◽  
Minzhou Luo ◽  
Tao Mei ◽  
Jianghai Zhao ◽  
Tao Li ◽  
...  

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