Autonomous robotic exploration of initially unknown environments is at the basis of several applications, including map building and search and rescue. Despite the many recent works on robotic exploration, an issue that has not been adequately addressed in the literature so far is the evaluation of the impact of the perception (for map update) and decision (about where to go next) timing on the behavior of an exploring robotic system. In this paper, we contribute to fill this gap by providing a quantitative experimental analysis of how frequencies of perception and decision influence the performance of an exploring mobile robot. Results, obtained with an experimental simulation framework (implemented and made publicly available) based on ROS and Stage, confirm the intuitive idea that the best performance is obtained with fast-paced perceptions and decisions, but also suggest some tradeoffs for the values of perception and decision frequencies in some settings.