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Article
Peer-Review Record

Central Pattern Generator with Defined Pulse Signals for Compliant-Resistant Control of Biped Robots

Biomimetics 2023, 8(1), 100; https://doi.org/10.3390/biomimetics8010100
by Zihan Xu 1,†, Qin Fang 1,†, Chengju Liu 1,2,* and Qijun Chen 1
Reviewer 1:
Reviewer 2: Anonymous
Biomimetics 2023, 8(1), 100; https://doi.org/10.3390/biomimetics8010100
Submission received: 18 January 2023 / Revised: 26 February 2023 / Accepted: 28 February 2023 / Published: 2 March 2023
(This article belongs to the Special Issue Bio-Inspired Design and Control of Legged Robot)

Round 1

Reviewer 1 Report

An article Central Pattern Generator with Defined Pulse Signals for Compliant-Resistant Control of Biped Robots is in subject of Biomimetics journal of MDPI

In article was proposed control strategy can generate defined pulse signals to realize compliant-resistant balance control for biped robots. It was checked by experiment using Nao robots.

This  valuable paper need minor review for improve found mistakes

You can find my remarks in few comments for consider iin your review

Comment 1

In Introduction you wrote using numbering

These are the main contributions of this paper.

1. A CPG pattern generator is proposed based on the Matsuoka’s CPG unit. It generates

the desired pulse signals required to achieve the compliant-resistant balance control for the biped robots; 106

2. A signal modulator is raised to map the output signals of the CPG model to the

workspace trajectory (when standing on double feet) or joint space trajectory (when standing on a single foot) of the biped robots;

3. A novelty method is proposed to design Matsuoka’s CPG to generate the pulse signals required;

4. The proposed control strategy is validated in the biped robot NAO simulation environments.

Because numbering is used for section better is use of bullet

These are the main contributions of this paper.

·         A CPG pattern generator is proposed based on the Matsuoka’s CPG unit. It generates the desired pulse signals required to achieve the compliant-resistant balance control for the biped robots;

·         A signal mo……….

·         …….

·         The proposed control strategy is validated in the biped robot NAO simulation environments

Comment 2

You prepare article based on 25 references. Please consider to add more references in scientific subject of article

Sensors 2022, 22(12), 4440; https://doi.org/10.3390/s22124440

Current  Robotics Report 2021, 2, 201–210; https://doi.org/10.1007/s43154-021-00050-9

Comment 3

You show

Figure 1. The architecture of the robot control system.

In Introduction

It need to move it to Section 2 after citation

Comment 4

You wrote

2. Control System Architecture

I propose use more detail name

2. Control System Architecture based on CPG

Comment 5

You present Section 3 as so large part of article which consist from 5 subsections

Please to consider add after

3. CPG-based Trajectory Generator

What you present in this section (based on titles of 5 subsections)

You wrote

The process of finding a parametric solution can be divided into the following steps:

1. Randomly generate an initial set of parameters;

2. Numerically integrate the CPG model under each parameter definition to obtain the time domain signal;

3. Evaluate the similarity of the obtained signal to the given signal characteristics, expressed in fitness;

4. Update parameters based on similarity;

5. Repeat the above process to get the parameter solution with the most prominent similarity.

I propose use of bullet for this part.  And also for this part

In order to obtain a signal with compliant-resistant characteristics, we believe that the time-domain signal integrated by the CPG model should have the following characteristics:

1. The signal can complete the compliance and resistance action process within a given time range and remain stable;

2. The signal can eventually decay to zero;

3. The signal should have a particularly high energy, which is specifically reflected in the fact that the output amplitude of the original signal cannot be too small. Otherwise, the control signal will not reflect the characteristics of compliance;

4. The time integral of the absolute value of the signal cannot be too large. The CPG output signal corresponds to the control quantity of the robot controller, and the integral result corresponds to the cumulative value of the control quantity output by the controller. It’s desired that the controller can use as little control quantity as possible to achieve the control result.

Command 6

You wrote

A fitness function defined using signal correlation is expressed as:

fitness =correlation/autocorrelation                                                                    (10)

Is it true?

Please consider to write

A fitness function defined using signal correlation and autocorrelation signals  is expressed as:

Comment 7

You wrote Section 5

5. Results

I propose change name of this section on

5. Results and discussion

because you both present and discuss results of experiments 

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

Using a central pattern generator model based on Matsuoki’s model Xu et al investigate the ability of a biped robot to maintain balance when exposed to an external perturbation.   The work is interesting and relevant. The manuscript is well-written. The figure caption could be improved. I have only minor comments, see below

 

Line 43: Suggesting an improvement of the sentence:  make humanoids not live up to the expectation of collaborating with humans and working in their environments. “ -> “make humanoids less suited for collaborating with humans and working in their environments.” 

 

Line 64 and onward:  Most of the traditional CPG models….” Could the authors comment on the new CPG model which has rotational dynamics to explain rhythmic hindlimb movement? See Linden et al Nature 2022 (https://www.nature.com/articles/s41586-022-05293-w). Here they find experimentally, as opposed to the Matsuoka’s model, that there aren’t really “flexor” or “extensor” interneurons, but rather neurons representing a continuum of phases throughout the cycle, hence rotational population dynamics. It would be good if the authors could comment on this perspective and whether this has an impact on the viability of the model proposed here.

 

Figure caption: In general I recommend using more active language.  The captions are all very short. Please help the reader more. 

Figure 1- I dont think this figure is self-explanatory. Please explain what is going on in the figure.

 

Figure 2- the caption is very short. Perhaps more explanation would help the reader. “Generated signal” by what and for what? What is the conclusion of the figure? Why is it important?

 

Figure 5 and 8: is there any difference between the images and what is going on? What does this show or prove?

 

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

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