In the last two months of TRAFCON, experiments for comparing the TRAFCON traffic manager and the traffic manager currently used by E80 have been carried on. Experiments have been done in the arena using three AGVs and two different layouts. The experiments have shown that the TRAFCON strategy works better than the E80 one from two main points of view. First, using TRAFCON more missions per hour can be executed; in the worst case roughly the same number of missions achieved by the E80 strategy are executed. Second, it is completely automatic, while the E80 strategy requires a lot of rules to be introduced manually.

In the last two months the experimental phase of the traffic control strategy developed in Task 2 in the arena built during Task 3 has been started. Given the size of the arena, 3 AGVs will be used to emulate realistic traffic situations. Several layouts and the corresponding roadmaps have been designed and the safety regions for the AGVs have been tuned. For each layout a set of missions to be executed by the AGVs on the roadmap has been defined. Several experiments have bee run using three AGVs on various layouts in order to check the presence of some inconsistencies of the traffic manager. The TRAFCON algorithm behaved as expected and a short movie of these experimental results has been uploaded in the Echord website. In the next months, the experimental campaign will be run. The efficiency of the TRAFCON control strategy will be evaluated and compared with the one that can be achieved using the traffic managed currently used by E80.

In the last two months, the traffic management strategy developed in a Matlab environment during Task 2 has been interfaced with the E80 architecture that controls the arena developed in Task 3. A UDP connection between a laptop running Matlab and the E80 control system has been established and the TRAFCON traffic manager receives and sends control data via UDP.

Furthermore, E80 staff has trained the UNIMORE staff  to use the supervisory system of the arena.

The routing strategy has been completed. It is based on an index evaluating the risk in terms of traffic of taking a given deviation. The risk factor measures the probability that a given path leads to a longer traveling time than the one of the path the AGV is traveling on. At each crossroad, an AGV computes the possible deviations and it chooses the one with lower risk.

The arena has been completed and tested using three AGVs. Now everything is ready for the experimental phase.

In the last two months, the TRAFCON team started to develop the planning strategy and proceeded with the construction of the arena.

For the path planning, two main situations have been considered: the startup and the online phase. At startup, where some waiting time is tolerated, an efficient but time consuming multi-robot planning strategy exploiting the traffic measure has been developed. For the online phase, where waiting time  is not be tolerated, a sub-optimal but computationally efficient planning strategy is being developed.

The localization system has been installed in the arena and some experiments have been run for testing it.