scholarly journals Optimization of Central Pattern Generator-Based Torque-Stiffness-Controlled Dynamic Bipedal Walking

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
William Suliman ◽  
Chadi Albitar ◽  
Lama Hassan
Keyword(s):  
Central Pattern Generator ◽  
Joint Stiffness ◽  
Biped Robot ◽  
Neural Model ◽  
Pattern Generator ◽  
Joint Torque ◽  
Performance Criteria ◽  
Bipedal Walking ◽  
Particle Swarm Algorithm ◽  
Input Control

In this paper, we propose a central pattern generator-based model to control the walking motion of a biped robot. The model independently controls the joint torque and joint stiffness in real time. Instead of the phase-dependent neural model used by Huang in 2014, we adopt the same structure for all the walking phases, reducing the number of connections between neurons. This reduction enables the employment of the particle swarm algorithm to find the optimal values of these parameters which lead to different solutions with different performance criteria. The simulation of the proposed method on a seven-link bipedal walking model gave a good performance in the range of walking speeds, which is referred to as versatility, and in walking pattern transition. The achieved walking gaits are 1-period cyclic motions for all the input control signals except for few gaits. Besides, these 1-period cyclic motions have a good local and global stability. Finally, we expanded our neural model by adding connections that work only when the robot walks on uneven terrains, which improved the robot’s performance against this kind of perturbation.

Gait Transition Control of a Biped Robot from Quadrupedal to Bipedal Locomotion Based on Central Pattern Generator, Phase Resetting, and Kinematic Synergy

2013 ◽  
pp. 11-24
Author(s):  
Shinya Aoi
Keyword(s):  
Control System ◽  
Central Pattern Generator ◽  
Biped Robot ◽  
Pattern Generator ◽  
Bipedal Locomotion ◽  
Phase Resetting ◽  
Gait Transition ◽  
Gait Patterns ◽  
Transition Control ◽  
The Stability

Recently, interest in the study of legged robots has increased, and various gait patterns of the robots have been established. However, unlike humans and animals, these robots still have difficulties in achieving adaptive locomotion, and a huge gap remains between them. This chapter deals with the gait transition of a biped robot from quadrupedal to bipedal locomotion. This gait transition requires drastic changes in the robot posture and the reduction of the number of supporting limbs, so the stability greatly changes during the transition. A locomotion control system is designed to achieve the gait transition based on the physiological concepts of central pattern generator, phase resetting, and kinematic synergy, and the usefulness of this control system is verified by the robot experiment.

scholarly journals Tegotae-Based Control Produces Adaptive Inter- and Intra-limb Coordination in Bipedal Walking

2021 ◽  
Vol 15 ◽  
Author(s):  
Dai Owaki ◽  
Shun-ya Horikiri ◽  
Jun Nishii ◽  
Akio Ishiguro
Keyword(s):  
Central Pattern Generator ◽  
Environmental Changes ◽  
Sensory Information ◽  
Motor Command ◽  
Pattern Generator ◽  
Bipedal Walking ◽  
Walking Robots ◽  
Two Dimensional ◽  
Limb Coordination ◽  
Systematic Methodology

Despite the appealing concept of central pattern generator (CPG)-based control for bipedal walking robots, there is currently no systematic methodology for designing a CPG-based controller. To remedy this oversight, we attempted to apply the Tegotae approach, a Japanese concept describing how well a perceived reaction, i.e., sensory information, matches an expectation, i.e., an intended motor command, in designing localised controllers in the CPG-based bipedal walking model. To this end, we developed a Tegotae function that quantifies the Tegotae concept. This function allowed incorporating decentralised controllers into the proposed bipedal walking model systematically. We designed a two-dimensional bipedal walking model using Tegotae functions and subsequently implemented it in simulations to validate the proposed design scheme. We found that our model can walk on both flat and uneven terrains and confirmed that the application of the Tegotae functions in all joint controllers results in excellent adaptability to environmental changes.

Dynamic bipedal walking of a dinosaur-like robot with an extant vertebrate's nervous system

Robotica ◽  
2013 ◽  
Vol 32 (6) ◽  
pp. 851-865 ◽  
Author(s):  
Yasuhiro Fukuoka ◽  
Junki Akama
Keyword(s):  
Nervous System ◽  
Pattern Generator ◽  
Joint Torque ◽  
Bipedal Walking ◽  
Control Methods ◽  
Walking Robot ◽  
Biologically Inspired ◽  
Walking Gait ◽  
And Control ◽  
Locomotion Rhythm

SUMMARYIn this study, we attempt to develop a biped dinosaur-like walking robot by focusing on its nervous system as well as its mechanism. We developed a robot ‘Dinobot’ on the basis of palaeontological knowledge on dinosaurs and extant animals. In addition, we employed typical biologically inspired walking gait generation and control methods derived from an extant vertebrate's nervous system. In particular, we utilized a central pattern generator (CPG), which is a locomotion rhythm generator in a vertebrate's spinal cord, to generate the robot's walking rhythm. Moreover, a reflex centre was placed below CPG and it produced joint torque of the legs in the swing and stance phases. Thus, we successfully achieved adaptive 3D dynamic walking generated by the interaction between the original mechanism of dinosaurs and the nervous system of extant animals. Our future goal is to find out a dinosaur's robust locomotive nervous system suitable for its mechanism.

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