Configurable Embedded CPG-Based Control for Robot Locomotion

Barrón-Zambrano, José Hugo; Torres-Huitzil, César; Girau, Bernard

doi:10.5772/50985

Cited by 14 publications

(6 citation statements)

References 14 publications

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“…Our work on IMT-NOs with bidirectional coupling is a marked departure from the past oscillator-based CPG implementation by Still et al 31 , who employed a chain of master-slave CMOS oscillators with unidirectional coupling. Finally, our computation approach leveraging collective dynamics of coupled oscillators provides an energy advantage compared to oscillator-based CPG models implemented on digital microcontroller (e.g., salamander robot developed by Ijspeert et al 32 ) and field-programmable gate array (FPGA) 33–38 .…”

Section: Resultsmentioning

confidence: 99%

Programmable coupled oscillators for synchronized locomotion

et al. 2019

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The striking similarity between biological locomotion gaits and the evolution of phase patterns in coupled oscillatory network can be traced to the role of central pattern generator located in the spinal cord. Bio-inspired robotics aim at harnessing this control approach for generation of rhythmic patterns for synchronized limb movement. Here, we utilize the phenomenon of synchronization and emergent spatiotemporal pattern from the interaction among coupled oscillators to generate a range of locomotion gait patterns. We experimentally demonstrate a central pattern generator network using capacitively coupled Vanadium Dioxide nano-oscillators. The coupled oscillators exhibit stable limit-cycle oscillations and tunable natural frequencies for real-time programmability of phase-pattern. The ultra-compact 1 Transistor-1 Resistor implementation of oscillator and bidirectional capacitive coupling allow small footprint area and low operating power. Compared to biomimetic CMOS based neuron and synapse models, our design simplifies on-chip implementation and real-time tunability by reducing the number of control parameters.

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Section: Resultsmentioning

confidence: 99%

Programmable coupled oscillators for synchronized locomotion

et al. 2019

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“…In these references, it cannot possible to appoint any time duration for condition of gait transition, so consequently, the robot is changed its gait suddenly at one predefined time. Alternatively, references like [13][14][15][16][17] utilized approach of coefficient matrix for each gait with ability to control the transition time, but any predefined setting function for directing or synchronizing the evolution of patterns between the gaits or adjusting parameters of the CPG are not existed. Finally, references like [20][21] used approaches which has only ability to adjust the duty factor of the gait in duration of the gait transition and generate different gaits.…”

Section: Discussionmentioning

confidence: 99%

“…Moreover, the speed and acceleration of swing legs at the time corresponding to the maximum height of the foot and also initial and final velocities of swing legs are set equivalent to zero. Constant terms in above equations can be obtained by applying double integration for both 𝑃 𝑥,𝑓𝑜𝑜𝑡(𝑖) and 𝑃 𝑧,𝑓𝑜𝑜𝑡(𝑖) directions, which are derived and computed as Equations (12)(13)(14)(15).…”

Section: Cartesian Footstep Plannermentioning

confidence: 99%

“…In this approach, each row and column of the matrix is associated to coupling coefficients between the oscillators, and the elements of matrix should be changed for gait adjusting at the desired time. Moreover, the references [13][14][15][16][17], used this coefficient matrix approach with both HOPF and Vander pol oscillator, but in all of these references, the gait of the robot without controlling speed or relative phases between the legs are changed suddenly at the predefined time. Many researchers have studied and classified different coupling approaches in order to achieve to diverse flexible spatial-temporal patterns [18].…”

Section: Introductionmentioning

confidence: 99%

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

Asadi¹,

Khorram²,

Moosavian³

2021

World J. Adv. Res. Rev.

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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.

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“…A large number of oscillator-based robotic CPG models have been constructed in these years. [18][19][20][21][22] Grzelczyk et al 23 investigated the prototype, control system architecture, and controlling of the hexapod legs with the CPG oscillator describing the nonlinear stick-slip-induced vibrations.…”

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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Configurable Embedded CPG-Based Control for Robot Locomotion

Cited by 14 publications

References 14 publications

Programmable coupled oscillators for synchronized locomotion

Programmable coupled oscillators for synchronized locomotion

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

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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