Development and Experimental Validation of Control Algorithm for Person-Following Autonomous Robots

Automatic guided vehicles, in particular, and industrial autonomous mobile robots, general, are commonly used to automate intralogistics processes. However, there certain logistic tasks, such as picking objects of variable sizes, shapes, physical characteristics, that very difficult handle fully automatically. In these cases, the collaboration between humans robots has been proven key for efficiency processes other applications. To this aim, it is necessary develop person-following robot solutions. work, we propose a autonomously controlling robotic interaction environments with unknown based on real experiments. do so, have developed an active tracking system control algorithm implement strategy automatic-guided vehicle. The analyzes cloud points measured by light detection ranging (LIDAR) sensor detect track target. From scan, estimates speed target obtain reference value calculates direction pure-pursuit algorithm. addition, enhance robustness solution, spatial temporal filters implemented discard obstacles crossings automatic Static dynamic test campaigns carried out experimentally validate approach autonomous-guided vehicle safety LIDAR.