Sensor Model Design of Range Sensor Based Probabilistic Localization for the Autonomous Mobile Robot

자율 주행 로봇의 확률론적 자기 위치 추정기법을 위해 거리 센서를 이용한 센서 모델 설계

This paper presents a sensor model design based on Monte Carlo Localization method. First, we define the measurement error of each sample using a map matching method by 2-D laser scanners and a pre-constructed grid-map of the environment. Second, samples are assigned probabilities due to matching errors from the gaussian probability density function considered of the sample's convergence. Simulation using real environment data shows good localization results by the designed sensor model.