Gait Generation With Smooth Transition Using CPG-Based Locomotion Control for Hexapod Walking Robot

Yu, Haitao; Gao, Haibo; Ding, Liang; Li, Mantian; Deng, Zongquan; Liu, Guangjun

doi:10.1109/tie.2016.2569489

Cited by 66 publications

(40 citation statements)

References 30 publications

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“…Although the main aim of this paper is to overcome the drawback that Matsuoka's CPG cannot generate rhythmic signals with desired shapes, this issue also exists in other kinds of CPG. Actually, the proposed framework is also feasible for other kinds of CPG (e.g., Hopf [40] and VDP [41]). It is because the irregular limit cycles of Hopf and VDP can also be transformed into the normalized limit cycle via feature processing, which can be subsequently used as the feature input of NN for learning to generate desired rhythmic signals.…”

Section: Discussionmentioning

confidence: 99%

Matsuoka’s CPG With Desired Rhythmic Signals for Adaptive Walking of Humanoid Robots

Wang

Xue

Chen

2020

IEEE Trans. Cybern.

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The desired rhythmic signals for adaptive walking of humanoid robots should have proper frequencies, phases, and shapes. Matsuoka's central pattern generator (CPG) is able to generate rhythmic signals with reasonable frequencies and phases, and thus has been widely applied to control the movements of legged robots, such as walking of humanoid robots. However, it is difficult for this kind of CPG to generate rhythmic signals with desired shapes, which limits the adaptability of walking of humanoid robots in various environments. To address this issue, a new framework that can generate desired rhythmic signals for Matsuoka's CPG is presented. The proposed framework includes three main parts. First, feature processing is conducted to transform the Matsuoka's CPG outputs into a normalized limit cycle. Second, by combining the normalized limit cycle with robot feedback as the feature inputs and setting the required learning objective, the neural network (NN) learns to generate desired rhythmic signals. Finally, in order to ensure the continuity of the desired rhythmic signals, signal filtering is applied to the outputs of NN, with the aim of smoothing the discontinuous parts. Numerical experiments on the proposed framework suggest that it can not only generate a variety of rhythmic signals with desired shapes but also preserve the frequency and phase properties of Matsuoka's CPG. In addition, the proposed framework is embedded into a control system for adaptive omnidirectional walking of humanoid robot NAO. Extensive simulation and real experiments on this control system demonstrate that the proposed framework is able to generate desired rhythmic signals for adaptive walking of NAO on fixed and changing inclined surfaces. Furthermore, the comparison studies verify that the proposed framework can significantly improve the adaptability of NAO's walking compared with the other methods.

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Section: Discussionmentioning

confidence: 99%

Matsuoka’s CPG With Desired Rhythmic Signals for Adaptive Walking of Humanoid Robots

Wang

Xue

Chen

2020

IEEE Trans. Cybern.

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“…[129] Techniques that promote uniform (rather than periodic or random) and energy-efficient locomotion are desirable from an engineering viewpoint as they provide maximum autonomy and power to other on-board systems, e.g., cameras or flow sensors. [132] Many of the best-known aquatic insects come from the true bugs (order Hemiptera), which includes water striders, water boatmen, backswimmers, and shore bugs. [126] Legs of insects in this order are well adapted to movement through water or on its surface.…”

Section: Swimming Adaptationsmentioning

confidence: 99%

It's Not a Bug, It's a Feature: Functional Materials in Insects

2018

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Over the course of their wildly successful proliferation across the earth, the insects as a taxon have evolved enviable adaptations to their diverse habitats, which include adhesives, locomotor systems, hydrophobic surfaces, and sensors and actuators that transduce mechanical, acoustic, optical, thermal, and chemical signals. Insect‐inspired designs currently appear in a range of contexts, including antireflective coatings, optical displays, and computing algorithms. However, as over one million distinct and highly specialized species of insects have colonized nearly all habitable regions on the planet, they still provide a largely untapped pool of unique problem‐solving strategies. With the intent of providing materials scientists and engineers with a muse for the next generation of bioinspired materials, here, a selection of some of the most spectacular adaptations that insects have evolved is assembled and organized by function. The insects presented display dazzling optical properties as a result of natural photonic crystals, precise hierarchical patterns that span length scales from nanometers to millimeters, and formidable defense mechanisms that deploy an arsenal of chemical weaponry. Successful mimicry of these adaptations may facilitate technological solutions to as wide a range of problems as they solve in the insects that originated them.

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“…6 Currently, the widely applied control methods for multi-joint robots include sliding mode control, 7 fuzzy control, 8 crossing-coupling control and contour error coupled control, [9][10][11] and central pattern generator (CPG) control. [12][13][14][15][16][17][18][19] Kamal et al 7 controlled TDFR's two joints to follow the two desired trajectories by applying the sliding mode control method. Combining proportional-integral-derivative (PID) control and fuzzy control, Mohan et al 8 controlled a TDFR to achieve the pre-appointed motions.…”

Section: Introductionmentioning

confidence: 99%

Central pattern generator–based coupling control method for synchronously controlling the two-degrees-of-freedom robot

Luo

Pan

et al. 2019

Science Progress

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Synchronous control is a fundamental and significant problem for controlling a multi-joint robot. In this article, by applying two coupled Rayleigh oscillators as the referred central pattern generator models for the two joints of a two-degrees-of-freedom robot, the central pattern generatorbased coupling control method is proposed for controlling the two-degrees-of-freedom robot's joints. On these bases, the co-simulation model of the two-degrees-of-freedom robot with the proposed central pattern generator-based coupling control method is established via ADAMS and MATLAB/Simulink, and the performance of the central pattern generator-based coupling control method on synchronizing two motions of two-degrees-of-freedom robot's joints is numerically simulated. Furthermore, the experimental setup of a two-degrees-of-freedom robot is established based on the real-time simulations system via the proposed central pattern generator-based coupling control method. And experiments are carried out on the established setup. Simulations and experimental results show that the phase of the controlled two-degreesof-freedom robot's joints is mutual locked to other, and their motion pattern can be adjusted through the coupling parameter in the central pattern generator-based coupling control method. In conclusion, the proposed central pattern generator-based coupling control method can control the two-degrees-of-freedom robot's joints to produce the coordinated motions and adjust the rhythmic pattern of the two-degrees-of-freedom robot.

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Gait Generation With Smooth Transition Using CPG-Based Locomotion Control for Hexapod Walking Robot

Cited by 66 publications

References 30 publications

Matsuoka’s CPG With Desired Rhythmic Signals for Adaptive Walking of Humanoid Robots

Matsuoka’s CPG With Desired Rhythmic Signals for Adaptive Walking of Humanoid Robots

It's Not a Bug, It's a Feature: Functional Materials in Insects

Central pattern generator–based coupling control method for synchronously controlling the two-degrees-of-freedom robot

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