01664nas a2200193 4500008003900000245010400039210006900143260004400212300001400256490006900270520096300339653002101302653001301323100001601336700001901352700001401371700001901385856006601404 2016 d00aIndoor Real-Time Localisation for Multiple Autonomous Vehicles Fusing Vision, Odometry and IMU Data0 aIndoor RealTime Localisation for Multiple Autonomous Vehicles Fu aRome, Italy, June 15-16, 2016bSpringer a288 - 2970 v9991 of the book series Lecture Notes in Computer Science (LNCS)3 a

Due to the increasing usage of service and industrial autonomous vehicles, a precise localisation is an essential component required in many applications, e.g. indoor robot navigation. In open outdoor environments, differential GPS systems can provide precise positioning information. However, there are many applications in which GPS cannot be used, such as indoor environments. In this work, we aim to increase robot autonomy providing a localisation system based on passive markers, that fuses three kinds of data through extended Kalman filters. With the use of low cost devices, the optical data are combined with other robots’ sensor signals, i.e. odometry and inertial measurement units (IMU) data, in order to obtain accurate localisation at higher tracking frequencies. The entire system has been developed fully integrated with the Robotic Operating System (ROS) and has been validated with real robots.

 

10aEmbedded Control10aRobotics1 aFaralli, A.1 aGiovannini, N.1 aNardi, S.1 aPallottino, L. uhttp://link.springer.com/chapter/10.1007/978-3-319-47605-6_24