Development of navigation system using slam and turtlebot 3 for waiter robot

Wan, Joe Yee (2021) Development of navigation system using slam and turtlebot 3 for waiter robot. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

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Abstract

Since the COVID-19 pandemic had occurred, our government began to ask individuals to follow the standard operating procedure (SOP) for COVID-19 prevention, such as applying social distance for one meter, regularly sanitizing your hands, etc. . One of the places many people visit is a restaurant. Since waiters serving food at the restaurant will still have direct contact with the customers, they will be the individu that can be categories having a high risk of getting an infection. In order to solve this issue, restaurant owners began using service robots as an option to help them to serve food for customers. To allow waiter robot operated well in the restaurant, a navigation system using SLAM have been developed for delivery the meal to customer table. Turtlebot 3 have been used as the hardware platform while Robot Operating System (ROS) is a software framework to develop navigation system for waiter robot. The testing enviroment for this experiment will be the map of the restaurant environmentgenerated by using Gmapping SLAM algorithm under different light inetensity during day time and night. Simulation in virtual world will be done for obtaining premilinary results for mapping environment and navigation. After that, the experiment on effect of light intensity to an environment have been conducted to study the light intensity in an environment will affect the accuracy of mobile robot to reach goal position. Experiment will be conducted in four conditions which are during daytime with high light intensity (Light is on), low intensity (Light is not turn on) and also night time with high light intensity (Light is on) ,low intensity(Light is not on). Based on the result , its shows that light intensity of an enviroment will affect the SLAM mapping process and this process will influnce the accuracy of the robot to reach desinagted goal positon. Gmapping SLAM mapping method will worked more accurately in an indoor enviroment with high light intensity enviroment where it could allow robot to reach goal destination correctly with averange accurracy rate up to 88% for both night and daytime condition than the indoor enviroment with low light intensity enviroment.

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