An Improved Positioning Accuracy Method of a Robot Based on Particle Filter
This work addresses positioning accuracy for indoor robots using laser navigation, but it is incremental as it applies an existing particle filter method to a specific scenario.
The paper tackled the problem of large positioning errors in robot navigation using laser range finders during fast movement or turning by proposing a particle filter method, resulting in an 85.5% improvement in positioning accuracy.
This paper aims to improve the performance and positioning accuracy of a robot by using the particle filter method. The laser range information is a wireless navigation system mainly used to measure, position, and control autonomous robots. Its localization is more flexible to control than wired guidance systems. However, the navigation through the laser range finder occurs with a large positioning error while it moves or turns fast. For solving this problem, the paper proposes a method to improve the positioning accuracy of a robot in an indoor environment by using a particle filter with robust characteristics in a nonlinear or non-Gaussian system. In this experiment, a robot is equipped with a laser range finder, two encoders, and a gyro for navigation to verify the positioning accuracy and performance. The positioning accuracy and performance could improve by approximately 85.5% in this proposed method.