scholarly journals Bio-inspired central pattern generator for development of Cartesian motor skills for a Quadruped Robot

2021 ◽  
Vol 12 (1) ◽  
pp. 066-085
Author(s):  
Farhad Asadi ◽  
Mahdi Khorram ◽  
S Ali A Moosavian

Central Pattern Generator (CPG) plays a significant role in the generation of diverse and stable gaits patterns for animals as well as controlling their locomotion. The main contributions of this paper are the ability to develop the Cartesian motor skills and coordinating legs of the quadruped robot for gait adaption and its nominal characteristics with CPG approach. Primary, a predefined relationship between an excitation signal and essential parameters of the CPG design is programmed. Next, the coordinated oscillator's rhythmic patterns by CPG and accordingly output gait diagrams for each foot of the robot are attained. Then, these desirable features such as predictive modulation and programming the gait event sequences including leg-lifting sequences and step length, duration of the time of each footstep within a gait, coordination of swing and stance phases of all legs are calculated in terms of different spatio_temporal vectors. Furthermore, a novel Cartesian footstep basis function is designed based on the robot characteristics and consequently, the associated spatio-temporal vectors can be inserted to it, which caused to spanning the space of possible gait timing in Cartesian space. Next, Cartesian footstep planner can be computed the swing foot trajectories in workspace along movement axes and then according to these footholds and feet placement, ZMP (Zero Moment Point) reference trajectory will be calculated and obtained. Therefore, COG (Center of Gravity) trajectory can be computed by designing a preview controller on the basis of the desired ZMP trajectory. Finally, to demonstrate the effectiveness of the proposed algorithm, it is implemented on a quadruped robot on both simulation or experimental implementations and the results are compared and discussed with other references.

2009 ◽  
Vol 06 (01) ◽  
pp. 33-46 ◽  
Author(s):  
LEI SUN ◽  
MAX Q.-H. MENG ◽  
SHUAI LI ◽  
HUAWEI LIANG ◽  
TAO MEI

This paper proposes a novel central pattern generator (CPG) model with proprioceptive mechanism and the dynamic connectivity mechanism. It not only contains the sensory information of the environment but also contains the information of the actuators and automatically tunes the parameters of CPG corresponding to the actuators information and inner sensory information. The position of the joints linked directly with the output of CPG is introduced to the CPG to find its proprioceptive system, spontaneously making the robot realize the actuator working status, further changing the CPG output to fit the change and decrease the influence of the problematic joints or actuators on the robot being controlled. So the damage would be avoided and self-protection is implemented. Its application on the locomotion control of a quadruped robot demonstrates the effectiveness of the proposed approach.


2012 ◽  
Vol 8 (1) ◽  
pp. 433-438 ◽  
Author(s):  
Bin Chen ◽  
Zhong-Cai Pei ◽  
Zhi-Yong Tang ◽  
Xiao-Qiang Guo ◽  
Hai-Xiao Zhong

Author(s):  
Victor Barasuol ◽  
Victor Juliano De Negri ◽  
Edson Roberto De Pieri

In this paper it is proposed a central pattern generator (CPG) based on workspace intentions, where the parameters of modulation have physical meaning and the walking can be adapted to overcome irregular terrains by changing few parameters. The walking features are independently modulated since there is no coupling relationship among WCPG parameters. Simulation results are presented to demonstrate the WCPG performance for a simplified quadruped robot model in different terrains.


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