Title :
Uniform Monte Carlo localization - fast and robust self-localization method for mobile robots
Author :
Ueda, Ryuichi ; Fukase, Takeshi ; Kobayashi, Yuichi ; Arai, Tamio ; Yuasa, Hideo ; Ota, Jun
Author_Institution :
Dept. of Precision Eng., Univ. of Tokyo, Japan
Abstract :
In this paper, we describe a novel self-localization algorithm. Self-localization methods are required for lowering the computational cost and handling vague sensor data. Thus, we propose to use only the uniform distribution to represent probability distributions in Monte Carlo localization, and name this method a uniform Monte Carlo localization (Uniform MCL). We manifest the low computational cost and robustness of Uniform MCL in the environment of RoboCup Sony legged robot league
Keywords :
Monte Carlo methods; mobile robots; position control; probability; self-adjusting systems; state-space methods; RoboCup; computational cost; mobile robots; probability distributions; state spaces; uniform Monte Carlo localization; vague sensor data; Computational efficiency; Intelligent robots; Legged locomotion; Mobile robots; Monte Carlo methods; Orbital robotics; Probability distribution; Robot sensing systems; Robustness; State-space methods;
Conference_Titel :
Robotics and Automation, 2002. Proceedings. ICRA '02. IEEE International Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-7272-7
DOI :
10.1109/ROBOT.2002.1014731
