Efficient implementation of FPGA based central pattern generator using distributed arithmetic

Li, Xiaojun; Li, Lin

doi:10.1587/elex.8.1848

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…Similarly, Barron-Zambrano et al explored the FPGA-based implementation of van de Pol oscillators coupled with a CPG controller to generate adaptive gait patterns for quadruped robots [143]. From the perspective of algorithm design, Li and Li exploited an improved distributed-arithmetic algorithm to maximize the usage of lookup tables in an FPGA-based CPG implementation [144]. Barron-Zambrano et al presented an FPGA-based embedded control scheme to connect the visual perception and the CPGbased locomotion [145].…”

Section: B Hardware Implementationmentioning

confidence: 99%

A Survey on CPG-Inspired Control Models and System Implementation

Tan

Chen

et al. 2014

IEEE Trans. Neural Netw. Learning Syst.

248

114

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This paper surveys the developments of the last 20 years in the field of central pattern generator (CPG) inspired locomotion control, with particular emphasis on the fast emerging robotics-related applications. Functioning as a biological neural network, CPGs can be considered as a group of coupled neurons that generate rhythmic signals without sensory feedback; however, sensory feedback is needed to shape the CPG signals. The basic idea in engineering endeavors is to replicate this intrinsic, computationally efficient, distributed control mechanism for multiple articulated joints, or multi-DOF control cases. In terms of various abstraction levels, existing CPG control models and their extensions are reviewed with a focus on the relative advantages and disadvantages of the models, including ease of design and implementation. The main issues arising from design, optimization, and implementation of the CPG-based control as well as possible alternatives are further discussed, with an attempt to shed more light on locomotion control-oriented theories and applications. The design challenges and trends associated with the further advancement of this area are also summarized.

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Section: B Hardware Implementationmentioning

confidence: 99%

A Survey on CPG-Inspired Control Models and System Implementation

Tan

Chen

et al. 2014

IEEE Trans. Neural Netw. Learning Syst.

248

114

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show abstract

“…Central pattern generators (CPGs) are intraspinal networks of neural oscillators capable of producing rhythmic output signals to control motor systems in part of animal locomotion [1]. Many mathematical models of CPGs have been proposed and analyzed so far [2,3,4,5,6,7,8]. Also, CPG models have been used to control artificial robots of various kinds [3,4,5,6,7,8] including snake-like robots [5,6,7,8] like the one in Fig.…”

Section: Introductionmentioning

confidence: 99%

A novel hardware-efficient CPG model based on asynchronous cellular automaton

Takeda

Torikai

2018

IEICE Electron. Express

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A novel hardware-efficient central pattern generator (CPG) model the dynamics of which is described by an asynchronous cellular automaton is proposed. It is shown that the proposed model can generate multi-phase synchronized periodic signals, which are suitable for controlling a serpentine motion of a snake-like robot. The proposed model is then implemented on a field programmable gate array (FPGA) and is used to control a snake-like robot. It is shown by experimental validation using a prototype machine that the proposed model can realize rhythmic locomotor activity in snakes. Moreover, it is shown that the proposed model consumes much fewer hardware resources (FPGA slices) than a typical conventional CPG model. Also, parameter setting methods to adjust the locomotion of the robot are shown.

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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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Efficient implementation of FPGA based central pattern generator using distributed arithmetic

Cited by 3 publications

References 7 publications

A Survey on CPG-Inspired Control Models and System Implementation

A Survey on CPG-Inspired Control Models and System Implementation

A novel hardware-efficient CPG model based on asynchronous cellular automaton

Programmable coupled oscillators for synchronized locomotion

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