This paper reports techniques that improve the performance of the sensors of an experimental autonomous agent, which travels on tracks, part of the PL-TOON platform. These small agents of the platform can be used to build a platooning experimental setup, as they are able to track a follower, measure their own speed and communicate wirelessly with other agents of the platoon, enabling the implementation of cooperative formation control strategies for teaching and research. The improvements to the embedded software of the agents presented here focus on calibrating the sensors and identifying a dynamical model for the agents, filtering noise, and removing erroneous measurements that can appear under unfavorable environmental conditions for the sensors. The techniques were validated through experiments which we also report in this work.