Skip to main content

Week 13: Software Configuration and Testing


For hardware construction: A simple camera holder was built to mount the camera with tripod.

For software construction: In these two weeks, we tried to embed the Roomba driving control and python audio into our detector code. Because of the port issue, we were not able to connect the Roomba to our original Linux VW. Therefore, we switched to other computers and platforms. The following are the platforms/computers that we tried and the reason why they were not able to complete our project goals. There are three major functions we are looking at: 

1. Can it run the mask detecor.py?

2. Can it install/support PyAudio?

3. Can it access Roomba's USB port and control the robot?

Table 1. System configuration and issues

Platform NameWhat it supportsWhat it does not supportWhy?
VMWare Linux VMMask detector, PyAudioRoomba driving controlUSB port could not be opened
Raspberry PiRoomba driving controlPyAudio, Mask detector"Arm-linux-gnueabihf-gcc" failed with exit status 1; Python version.
CONDA JupiterTo be testedThe terminal was removed from the software and need to be redownloadedThe system upgrade removes the terminal from its windows
Mac PyCharmRoomba driving control, (mask detector)PyAudioCommand errored out with exit status 1
Virtue box ubuntuPyAudioMask Detector python version not support
Linux DUO systemTo be testedTo be testedTo be tested

We also programmed the Roomba driving control following Dr. Byung-Cheo Min's lecture slide - Programmable Robot System II, and the PyAudio speech assistant by Brad Traversy. 

WHAT IS NEXT: 

  • As installing the PyAudio package is a major issue in most platforms (error message see below), and we tried troubleshooting that is available online, if it is still not working by the end of this week, we should consider abandon the voice assistant and use Roomba audio instead. 


  • If we could fix the port issue for our VM (which should be the easiest approach), we can combine our driving control with the detector and the speaking program. If not, either the Linux DUO system or Pycharm will be an alternative way.
  • We need to do multiple testing to calculate the time for the robot to move from one point to the other and the distance for it to move forward if people are not wearing the mask. 
  • Combine all the functions into one single python file and test it!
  • Preparing for the project presentation next Thursday.
References: 
  1. alexis_speech_assistant by Brad Traversy (https://github.com/bradtraversy/alexis_speech_assistant)
  2. Programmable Robot System II. pdf by Dr. Byung-Cheo Min 

Comments

Post a Comment

Popular posts from this blog

Week 9: Project Literature Review & Methodology

L ITERATURE R EVIEW A. The Importance of Mask during COVID-19 In order to slow the spread of COVID-19, limiting physical distancing and using other measurements to decrease the transmission probability are necessary. According to J. Howard et al., if face masks were used by all household members prior to symptoms occurring, it has a 79% effective rate in preventing transmission. Besides, the states with mask mandates to require residents to wear a mask have a lower daily growth rate than those without. As a mask provides a physical barrier that reduces the spread of respiratory droplets and particles into the air, properly wearing a mask can protect the safety of everyone [1]. Figure 1 : The efficiency of mask in blocking the virus B. The Implementation of Mask Detection Robot Currently, mask and temperature detection robots have shown their important role in responding to the COVID-19 pandemic. The U...
Post a Comment
Read more

Week 11: Robot Hardware Building and the Implementation of Face Mask Detection

  What we finished in these two weeks: Hardware for the robots We have used a tripod to hold the mobile camera. Figure 1&2 demonstrate the graphic design of the robot and how it actually looks like. A 10 ft extension USB cable will be used to connect the camera and the computer We estimated the observation distance between the robot and passengers. Between 1.3 meters to 1.5 meters, the robot is able to observe two passengers at once. Figure 1: The hardware design of face mask detection robot Figure 2: How the robot looks like in reality Implementing the face mask detector We applied the face mask detector designed by  Chandrika Deb , which has a 98% accuracy for Face Mask Detection after training via TensorFlow-gpu==2.5.0 The framework used by the detector:  OpenCV Caffe-based face detector Keras TensorFlow MobileNetV2 A short demo video of us testing the face mask detector can be found below. Video 1: Testing the real-time video stream mask detecting Reference: ...
Post a Comment
Read more

Week 7: Introduction

  Project Introduction      In December 2019, the first case of COVID-19 was discovered in Wuhan, China. As of March 11, 118M cases were reported worldwide. In order to help slow the spread of coronavirus, CDC recommends people wear masks in public settings. Starting from February 2, 2021, face masks are required in all forms of public transportation traveling , such as bus, train, and plane. To protect the safety of passengers, in this project, we plan to build a service robot that is able to check the mask-wearing in a public transportation scenario. The robot will act as a security patrol robot and identify the passenger without a face mask immediately.  Photo: JEENAH MOON/BLOOMBERG NEWS Project Objectives The robot is able to scan passengers The robot is able to detect if passengers wear facemasks or not The robot is able to move towards the passengers without masks The robot is able to check passenger's temperature The Robot Flowchart Project Plan Week 7~8:...
Post a Comment
Read more