Mini-Project II Monte Carlo Localisation for mobile robots

The localisation is not a trivial problem of mobile robotics. The robot must localise itself, having merely a map of the environment and sensor readings. This is a base knowledge that robot must possess in order to be able to complete higher level tasks like path planning. The Monte Carlo Localisation (MCL) is a probabilistic algorithm successfully applied in many mobile robot systems. The core of the system that implements the MCL algorithm is the “T1000” Java-written robot application platform which cooperates with the “Saphira” robot control system developed at SRI International’s Artificial Intelligence Center. T1000 is a client application communicating via TCP/IP network with a Windows/Linux server for Saphira, what enables running and testing several robot applications at the same time. Thanks to affine transformation of robot’s sensor measurements, the algorithm does not have to be synchronised with incoming sensor data, and allows processing several measurements at a time. Moreover, they can be processed at any convenient time, what simplifies using any preselection algorithm. In addition, the improved particles’ initialisation can also reduce the number of particles without decreasing the effectiveness of the basic MCL algorithm. Even though the system was not tested yet on real robots, the experiments with the “Pioneer” robot simulator are promising, and it seems that the system is comparable to the original MCL software attached to Saphira.