CPG-based autonomous swimming control for multi-tasks of a biomimetic robotic fish

Rhythm motion control in bio‐inspired fishtail based on central pattern generator

“…The chain or ring network coupled with CPGs [14] is relatively common coupling method. In terms of natural phenomena, the individual behaviours may be affected via the physical mediums, which generates from the behaviours for others, such as the locomotion of animal gaits [3][4][5][6][11][12][13][14]18] and symmetry in locomotor and animal gaits [20], where one gait can have an effect on the other part via neural systems. Essentially, a number of neural systems that focus on the coupling relationship of CPGs are treated as arrays of coupled oscillators with characteristic phase coupling [21].…”

“…While many biologists indicate that rhythmic motion control can be generated from the central pattern generators (CPGs) [10], which are networks of non-linear oscillating neurons capable of producing coordinated patterns of rhythmic activities without giving explicit control input signals with respect to the time variables [11]. At present, the primary approach of bionic rhythm control is to use the CPG in robotics to obtain coordinated, stable and adaptable rhythm motions [11] since rhythms are generated centrally without requiring sensory information for example the snake-like robots [12], the fish-like robots [3,4,7], the humanoid robot [13], the quadruped [5], the hexapod-like robot [14], and the classic salamander-like robot [6], etc.…”

“…[1,2]. In recent years, we have witnessed extensively considerable developments of the bionic aquatic robots and the robot bio-fish [3][4][5][6][7]. Motivated by aquatic animals, a variety of models for biomimetic robots have been proposed by a number of researchers and scientists, focussing not only on the configuration design of vehicles but also on bio-inspired swimming and motion control [8,9].…”

Inverse-model intelligent control of fin-actuated underwater robots based on drag force propulsion

“…Fin-actuated underwater vehicles [15] usually control motion by changing the locomotion primitives of the fins, such as frequency, amplitude, phase shift, or in more complicated cases also the angle of attack, stiffness or surface area. Previously, fin-actuated robots have been controlled using adaptive control [19], PID control [6], RISE control [4], fuzzy logic control [23], prioritization-based control [24] and bio-inspired CPG control [36,3].…”

Research on Motion Mode Switching Method Based on CPG Network Reconstruction

“…The motion control of the bionic fish is a typical representative of multi-DOF coordinated control, so CPG control is increasingly being applied to the motion control of the bionic fish [7]- [9]. Cafer Bal et al proposed a finite state machine based on fuzzy control, which can adjust the CPG output according to different feedback information, so that the robot fish has good ability of autonomous obstacle avoidance [10]. Junzhi Yu, Wang Ming et al optimized the output parameters of CPG through particle swarm optimization, improved the propulsion efficiency and speed of the robot fish, and explored the effect of CPG characteristic parameters on energy consumption during the swimming process of the robot fish [11]- [13].…”