Biomimetic Motion Control System Based on a CPG for an Amphibious Multi-Link Mobile Robot

Matsuo, Takayuki; Yokoyama, Takeshi; Ueno, Daishi; Ishii, Kazuki

doi:10.1016/s1672-6529(08)60078-5

Cited by 26 publications

(14 citation statements)

References 9 publications

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“…Signals in 0~8 s illustrate the slow hexapod gait, signals in 8~16 s illustrate the slow tripod gait, and signals in 16~20 s illustrate the fast tripod gait. When φ 1,2 , φ 1,4 and φ 1,6 have been changed to π, Leg 1, 3 and 5 rotate gradually to achieve an opposite phase to Leg 2, 4 and 6 to form a tripod gait. The whole transition process sustains about 2 periods, and if the locomotion speed is higher, time consumption of this gait transition will be reduced.…”

Section: Gait Transition With the Application Of Cpgmentioning

confidence: 99%

“…AQUA2 with replaceable flipper legs has been developed to transition between locomotion modes [3]. Snake-like robots, such as ACM-R5 [4], can propel on land and underwater by undulating their bodies, which are another representative amphibious robots [4][5][6]. Salamander amphibious robot (Salamander Robot) can utilize body undulation and limb walking to transit between terrestrial and aquatic locomotion [7,8].…”

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confidence: 99%

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On a CPG-Based Hexapod Robot: AmphiHex-II With Variable Stiffness Legs

Zhong

Zhang

et al. 2018

IEEE/ASME Trans. Mechatron.

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Amphibious robots have attracted more and more attention from researchers for their broad applications, while it also brings great challenges in designing appropriate propulsion mechanisms and effective control algorithms. In this paper, we reported a newly designed amphibious hexapod robot-AmphiHex-II. This robot possesses six newly designed variable stiffness legs for adapting various complex environments. This novel design of the variable stiffness leg seamlessly incorporates the advantages of both semi-circular walking legs and the swimming flexible flippers. The legs are constructed by rigid fan-shaped frames which work as walking legs for terrestrial locomotion and protect the contained flexible flippers used for aquatic locomotion during terrestrial operations. The stiffness of legs can be adjusted to an effective degree by adjusting the positions of sliders manually. The effect of variable stiffness on locomotion performance was experimentally investigated. Moreover, in order to achieve a smooth and quick gait transition, a Central Pattern Generator (CPG) neural network was introduced to control the system. Different gait generation strategies on land and underwater were demonstrated. A series of field experiments were carried out to evaluate locomotion performance of the AmphiHex-II for terrestrial and aquatic mobility, and the results demonstrate the advantages of the novel leg design and the control system.

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Section: Gait Transition With the Application Of Cpgmentioning

confidence: 99%

mentioning

confidence: 99%

On a CPG-Based Hexapod Robot: AmphiHex-II With Variable Stiffness Legs

Zhong

Zhang

et al. 2018

IEEE/ASME Trans. Mechatron.

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“…The CPG coupling architecture was taken from [25] (Fig. 5), and the architecture is arranged so that the extensor neuron of a given CPG is coupled to the flexor neuron of its neighboring CPGs.…”

Section: B Design Requirements and Implementation Of Oscillator Modelmentioning

confidence: 99%

Biologically derived models of the sunfish for experimental investigations of multi-fin swimming

Tangorra

Mignano

Carryon

et al. 2011

2011 IEEE/RSJ International Conference on Intelligent Robots and Systems

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The remarkable swimming abilities of bony fish are the result of multiple interacting subsystems, each tuned to perform certain roles. These subsystems, which include the statically unstable body, multiple highly actuated fins, oscillatory neural controllers, and distributed senses, are not often studied as mutually dependent systems. This research program is developing biorobotic models of these systems and integrating the systems into a biorobotic fish so that interdependencies can be explored during free swimming. The robot body was derived from a bluegill sunfish, and has a tunable mass distribution and a mixture of rigid and flexible sections so that dynamical characteristics of the fish body can be explored. Five highly deformable fins have structural properties scaled to those of biological fins and can create gait patterns for steady swimming and maneuvers. A first generation artificial CPG has been programmed for each fin on a network of five low power microcontrollers. Finally, a dedicated biorobotic pectoral fin has been developed and instrumented with distributed sensory systems so relevant physical (e.g., fin curvature) and hydrodynamic (e.g., pressure) data can be identified and used to predict fin force for closed loop control.

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“…In order to mimic fish-like undulating propulsion, Ding et al 21 and Yu et al 36 designed a CPG-based control architecture consisting of coupled oscillators and successfully used it to control the swimming gaits of an amphibious robot propelled by modular fish-like propelling units and a pair of hybrid wheel-propeller-fin mechanisms. In order to control the manipulation of a multi-link amphibious robot in extreme environments, Matsuo et al 37 proposed a CPG-based biomimetic neural system that is sufficiently robust and strong to cope with disturbance and breakdowns. Ijspeert and Crespi 38,39 presented a locomotion controller based on the biological concept of CPGs together with a gradient-free optimization method and employed it to optimize the gait of an amphibious snake/lamprey robot online.…”

Section: Introductionmentioning

confidence: 99%

Central pattern generator and feedforward neural network-based self-adaptive gait control for a crab-like robot locomoting on complex terrain under two reflex mechanisms

Wang

Chen

Han

2017

International Journal of Advanced Robotic Systems

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Although quite a few central pattern generator controllers have been developed to regulate the locomotion of terrestrial bionic robots, few studies have been conducted on the central pattern generator control technique for amphibious robots crawling on complex terrains. The present article proposes a central pattern generator and feedforward neural networkbased self-adaptive gait control method for a crab-like robot locomoting on complex terrain under two reflex mechanisms. In detail, two nonlinear ordinary differential equations are presented at first to model a Hopf oscillator with limit cycle effects. Having Hopf oscillators as the basic units, a central pattern generator system is proposed for the waveform-gait control of the crab-like robot. A tri-layer feedforward neural network is then constructed to establish the one-to-one mapping between the central pattern generator rhythmic signals and the joint angles. Based on the central pattern generator system and feedforward neural network, two reflex mechanisms are put forward to realize selfadaptive gait control on complex terrains. Finally, experiments with the crab-like robot are performed to verify the waveform-gait generation and transition performances and the self-adaptive locomotion capability on uneven ground.

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Biomimetic Motion Control System Based on a CPG for an Amphibious Multi-Link Mobile Robot

Cited by 26 publications

References 9 publications

On a CPG-Based Hexapod Robot: AmphiHex-II With Variable Stiffness Legs

On a CPG-Based Hexapod Robot: AmphiHex-II With Variable Stiffness Legs

Biologically derived models of the sunfish for experimental investigations of multi-fin swimming

Central pattern generator and feedforward neural network-based self-adaptive gait control for a crab-like robot locomoting on complex terrain under two reflex mechanisms

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