Robot Bionic Eye Motion Posture Control System

Round 1

Reviewer 1 Report (Previous Reviewer 2)

I really appreciate the huge effort made by the authors. This form of paper is recommended for publication

Author Response

Thank you very much for your recommendation!

Reviewer 2 Report (Previous Reviewer 1)

Dear Authors,

1.       The robotic bionic vision has progressed less percentage till date, we are appreciating authors for their contribution in achieving best results, in lines of low-power consumption for bionic eye movement and posture system.

2.       The Author's team defined, regarding power consumption while using various IMU for robotic bionic eye motion with posture control system.

3.        As per results, MPU9250 consumes less power 3.28mA comparatively with other methods such as MPU6050 and WT9011G4K.

4.       As per software flow analysis it takes 15m/s.

5.       The EKF algorithm was preferred in this process due to less error percentage.

 

Questions to authors

1.       As per figure 5, What is the random process data rate at IMU.

2.       How the team synchronized both acceleration & angular velocity and image control system, any control algorithms are contributed, if yes please keep some light on the concept.

3.       Figure 18 represents the posture correction systems in interference. Authors are requested to figure out the relation between research contribution versus Bundle Adjustment (BA), epipolar geometry used while evaluating pose estimation. 

 

Author Response

Questions  

1. As per figure 5, What is the random process data rate at IMU?
Response: Thank you very much for your question. IMU random process data rate is 200Hz. Under LowPower mode, it is 31.25Hz.

2. How the team synchronized both acceleration & angular velocity and the image control system, and any control algorithms contributed, if yes please keep some light on the concept.
Response: Thank you very much for your question. Because this experiment is mainly to study the low-power effects of bionic eye movement and posture system, the common RGB-D algorithm is omitted. Now I would like to add that, first of all, when the binocular camera collects images, they will be transmitted to the image control system, which can adopt YOLO. The image control system commands the drive control system, and drives the motor to rotate so that the eyeball can realize the target tracking; In the process of eye movement, the IMU will transmit the attitude data to the attitude control system, and the attitude control system will conduct the EKF data fusion, to realize the control with high precision.

3. Figure 18 represents the posture correction systems in interference. Authors are requested to figure out the relation between research contribution versus Bundle Adjustment (BA), and epipolar geometry used while evaluating pose estimation.
Response: That's a great question! The posture correction system has nothing to do with (BA), which was not shown in FIG. 18 at the beginning. However, since a bionic eye is needed in a SLAM project, we conducted vibration interference while running the SLAM project to observe the balance of the posture correction system, and found that it had a good effect after opening.

This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.

Round 1

Reviewer 1 Report

Dear Authors, It is interesting for your research attempt.

1. Authors have mentioned, Kalman filter based algorithms  has been proposed for data fusion. Real time data fusion results are missing in the results section. Only math lab and data set related results incorporated.

2.  Researchers not defined any timing analysis and power consumption in lines of embedded systems using STM32F103C8T6 device. 

3. Correlate, or elaborate your work impact on camera pose estimation analysis. How far your work supports existing Bundle adjustment analysis in pose estimation. 

4. Comparative results are not furnished with respect to the binocular vision system.   

Remaining part of a paper presented well. 

 

 

Reviewer 2 Report

Please see the attached file

Comments for author File: Comments.pdf