scholarly journals Generation of Suitable Jumping Motion Pattern for Hopping Robot under Genetic Algorithm

2000 ◽  
Vol 120 (10) ◽  
pp. 1365-1371
Author(s):  
Yoshida Yoshiro ◽  
Kamano Takyua ◽  
Yasuno Takashi ◽  
Suzuki Takayuki ◽  
Harada Hironobu ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Motion Pattern ◽  
Hopping Robot

Generation of jumping motion pattern for a hopping robot using genetic algorithm

2000 ◽  
Vol 4 (1) ◽  
pp. 31-36 ◽  
Author(s):  
Yoshiro Yoshida ◽  
Takuya Kamano ◽  
Takadhi Yasuno ◽  
Yu Kataoka
Keyword(s):  
Genetic Algorithm ◽  
Motion Pattern ◽  
Hopping Robot

Models of a hybrid wheeled hopping self-balanced robot

2021 ◽  
pp. 095440622098419
Author(s):  
Qimin Li ◽  
Haibing Zeng ◽  
Long Bai ◽  
Zijian An
Keyword(s):  
Pid Control ◽  
Motion Pattern ◽  
System Dynamics Model ◽  
Dynamics Model ◽  
Swarm Optimization ◽  
Hopping Robot ◽  
Control Scheme ◽  
Hopping Robots ◽  
Hybrid Motion ◽  
Classical Control

Combining wheeled structure with hopping mechanism, this paper purposes a self-balanced hopping robot with hybrid motion pattern. The main actuator which is the cylindrical cam, optimized by particle swarm optimization (PSO), is equipped with the motor to control the hopping motion. Robotic system dynamics model is established and solved by Lagrangian method. After linearization, control characteristics of the system is obtained by classical control theory based on dynamics equations. By applying Adams and Matlab to simulate the system, hopping locomotion and self-balanced capability are validated respectively, and result shows that jump height can reach 750 mm theoretically. Then PID control scheme is developed and specific models of hardware and software are settled down accordingly. Finally, prototype is implemented and series of hopping experiments are conducted, showing that with different projectile angle, prototype can jump 550 mm in height and 460 mm in length, transcending majority of other existing hopping robots.

Search for Initial Conditions for Sustained Hopping of Passive Springy-Leg Offset-Mass Hopping Robot

2007 ◽  
Vol 129 (4) ◽  
pp. 522-526 ◽  
Author(s):  
B. Seth ◽  
P. Seshu ◽  
P. V. Shanmuganathan ◽  
V. V. Vichare ◽  
P. Raj
Keyword(s):  
Genetic Algorithm ◽  
Search Strategy ◽  
Initial Conditions ◽  
Center Of Gravity ◽  
The Body ◽  
Hopping Robot ◽  
Spring Force

A springy-leg, offset-mass or SLOM hopper configuration is considered here, wherein the center of gravity of the body is offset from the line of action of spring force. It is observed that this feature tends to extend the passive hopping motion. A heuristics-based search strategy and a genetic algorithm-based search strategy are implemented for finding the initial conditions that result in extended hopping motion.

scholarly journals PI/backstepping control of snake robot optimazed by genetic algorithm

2014 ◽  
Vol 3 (2) ◽  
pp. 99 ◽  
Author(s):  
Maryam Jafari ◽  
Aref Shahmansoorian
Keyword(s):  
Genetic Algorithm ◽  
Robust Control ◽  
Sliding Mode ◽  
Tracking Error ◽  
Backstepping Control ◽  
Control Parameters ◽  
Motion Pattern ◽  
Snake Robot ◽  
The Stability ◽  
And Control

This paper describes the design of robust control of PI/Backstepping for the snake robot to control the joints motion. First, the stability of the method is proved and, by applying this controller to the robot, its motion pattern is controlled in a way that it can move and follow by mimicking the motion of real snakes on the predefined trajectories. Then, the control parameters are optimized using the Genetic Algorithm (GA). Comparing obtained results with sliding mode revealed that, the former has significantly reduced the tracking error and control energy; in addition there is no chattering phenomenon. Keywords: Snake Robot, PI/Backstepping Control, Genetic Algorithm, Control Energy.

scholarly journals Optimizing central pattern generators (CPG) controller for one legged hopping robot by using genetic algorithm (GA)

2018 ◽  
Vol 7 (2.14) ◽  
pp. 160 ◽  
Author(s):  
Arman Hadi Azahar ◽  
Chong Shin Horng ◽  
Anuar Mohamed Kassim ◽  
Amar Faiz Zainal Abidin ◽  
Mohamad Haniff Harun ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Stochastic Optimization ◽  
Central Pattern Generators ◽  
Optimization Method ◽  
Pattern Generator ◽  
Pi Controller ◽  
Optimum Parameters ◽  
Hopping Robot ◽  
Pattern Generators ◽  
The One

This paper presents the optimization process of Central Pattern Generator (CPG) controller for one legged hopping robot by using Genetic Algorithm (GA). To control the one legged hopping robot, a CPG controller is designed and integrated with a conventional Proportional-Integral (PI) controller. Conventionally, the CPG parameters are tuned manually. But by using this method, the parameters produced are not exactly the optimum parameters for the CPG. Therefore, a computational stochastic optimization method; GA is designed to optimize the CPG controller parameters. The GA is designed based on minimizing the error produced towards achieving the reference height. The re-sponse of the one legged hopping robot is compared and the results of the error towards reference height are analyzed.  

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