Galloping trajectory optimization and control for quadruped robot using genetic algorithm

2007 ◽  
Author(s):  
Giju Chae ◽  
Jong Hyeon Park
Keyword(s):  
Genetic Algorithm ◽  
Trajectory Optimization ◽  
Quadruped Robot ◽  
Optimization And Control ◽  
And Control

scholarly journals Online Dynamic Trajectory Optimization and Control for a Quadruped Robot

2021 ◽  
Author(s):  
Oguzhan Cebe ◽  
Carlo Tiseo ◽  
Guiyang Xin ◽  
Hsiu-chin Lin ◽  
Joshua Smith ◽  
...  
Keyword(s):  
Trajectory Optimization ◽  
Quadruped Robot ◽  
Optimization And Control ◽  
And Control ◽  
Dynamic Trajectory

scholarly journals Genetic Algorithm Optimization and Control System Design of Flexible Structures

2008 ◽  
Vol 17 (Supplement) ◽  
Author(s):  
M.O. Tokhi ◽  
M.Z. Md Zain ◽  
M.S. Alam ◽  
F.M. Aldebrez ◽  
S.Z. Mohd Hashim ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Control System ◽  
System Design ◽  
Flexible Structures ◽  
Control System Design ◽  
Algorithm Optimization ◽  
Genetic Algorithm Optimization ◽  
Optimization And Control ◽  
And Control

Hybrid IWD-GA: An Approach for Path Optimization and Control of Multiple Mobile Robot in Obscure Static and Dynamic Environments

Robotica ◽  
2021 ◽  
pp. 1-28
Author(s):  
Saroj Kumar ◽  
Dayal Ramakrushna Parhi ◽  
Krishna Kant Pandey ◽  
Manoj Kumar Muni
Keyword(s):  
Genetic Algorithm ◽  
Path Length ◽  
Water Drop ◽  
Optimal Path ◽  
Dynamic Environments ◽  
Path Optimization ◽  
Matlab Simulation ◽  
Optimization And Control ◽  
Global Optimal ◽  
And Control

SUMMARY In this article, hybridization of IWD (intelligent water drop) and GA (genetic algorithm) technique is developed and executed in order to obtain global optimal path by replacing local optimal points. Sensors of mobile robots are used for mapping and detecting the environment and obstacles present. The developed technique is tested in MATLAB simulation platform, and experimental analysis is performed in real-time environments to observe the effectiveness of IWD-GA technique. Furthermore, statistical analysis of obtained results is also performed for testing their linearity and normality. A significant improvement of about 13.14% in terms of path length is reported when the proposed technique is tested against other existing techniques.

scholarly journals Performance Comparisons of Bio-micro Genetic Algorithms on Robot Locomotion

2020 ◽  
Author(s):  
Francisco A. Chávez-Estrada ◽  
Jacobo Sandoval-Gutierrez ◽  
Juan C. Herrera-Lozada ◽  
Mauricio Olguín-Carbajal ◽  
Daniel L. Martínez-Vázquez ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Embedded System ◽  
Processing Time ◽  
Quadruped Robot ◽  
Robot Locomotion ◽  
Real Performance ◽  
The Individual ◽  
Computational Resources ◽  
And Control ◽  
Better Than

This paper presents a novel micro-segmented genetic algorithm (μsGA) to identify the best solution for the locomotion of a quadruped robot designed on a rectangular ABS plastic platform. We compare our algorithm with three similar algorithms found in the specialized literature: a standard genetic algorithm (GA), a micro-genetic algorithm (μGA), and a micro artificial immune system (μAIS). The quadruped robot prototype guarantees the same conditions for each test. The platform was developed using 3D printing for the structure and can accommodate the mechanisms, sensors, servomechanisms as actuators. It also has an internal battery and a multicore embedded system (mES) to process and control the robot locomotion. This research proposes a μsGA that segments the individual into specific bytes. μGA techniques are applied to each segment to reduce the processing time; the same benefits as the GA are obtained, while the use of a computer and the high computational resources characteristic of the GA are avoided. This is the reason why some research in robot locomotion is limited to simulation. The results show that the performance of μsGA is better than the three other algorithms (GA, μGA and AIS). The processing time was reduced using a mES architecture that enables parallel processing, meaning that the requirements for resources and memory were reduced. This research solves the problem of continuous locomotion of a quadruped robot, and gives a feasible solution with real performance parameters using a μsGA bio-micro algorithm and a mES architecture.

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