Performance analysis of Adaptive Monte Carlo Localization (AMCL) algorithm using Robot Operating System (ROS)

Sijamsir, Muhammad Safie (2022) Performance analysis of Adaptive Monte Carlo Localization (AMCL) algorithm using Robot Operating System (ROS). Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

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Abstract

Robot Operating System (ROS) is a new concept of robot software platform which is commonly used worldwide for controlling robots. In the current mobile robot application, there are several problems arise. One of the problems is to estimate the robot position and orientation within the environment or map using information gathered from the sensors. In this report, the performance analysis of Adaptive Monte Carlo Localization (AMCL) is being conducted. AMCL is one of the localization algorithms for robot to localize using a particle filter. To optimize the AMCL algorithm, there are several parameters need to be investigated such as the number of particles, threshold for selective resampling and resolution of grid map that can affect the performance of the AMCL algorithm. In this project, the performance of AMCL algorithm will be analysed. The result obtained shows that with 10000 max number of particles has higher accuracy and lower error compared to 3000 max number of particles. In conclusion, the higher the number of particles, the higher the accuracy and the lower the robot pose error.

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