t-bots: a coordinated team of mobile units for searching and occupying a target area at unknown location


t-bots is the team of simulated robotic units developed at the Robotics Laboratory of the University of Pavia for participating to the simulated contest of CiberMouse’08.

t-bots is a team of co-ordinated mobile units designed for the collaborative search of a target goal at unknown location within a workspace where obstacles limit the mobility of robots. The final goal of the team is to make all the team robots to reach the final target location and to enter a delimited target area. The strategy of each robot depends on the information that are gathered during the exploration. Such information can be acquired by sampling onboard sensors or can be received from other mobile units, thus exploiting the communication capabilities of robots.

A Finite State Machine (FSM) determines the mobility strategy, the co-ordination and operational modes. The FSM’s state change is triggered by the information collected by the robots and by the information received from other robots using wireless communication devices.


t-bots are implemented in C (what else? :-)). They feature some good characteristics but has also some known but not yet fixed bugs. This is due tu the lack of time for testing and fine tuning, and hopefully I will deal with those issues in the next future.

Anyone who download the code, use it and detect some problems, is highly invited to drop me an e-mail.

Relevant features

Known issues

The competition

t-bots won the second prize at the official competition.

t-bots performed very well during the competition. The robotic team won with large discard the first two stages, allowing in both cases 4 of the total 5 robots to enter the target area, while the remaining one was just outside the area.

One of the most effective strategy consisted in gradually increase the robot speeds, starting with very low speed to spread the robots, and increasing the speed after a while, when robots would not interfere anymore each other.

The entering strategy was not used, since the short time available per each run did not suggested to keep the robots alive when inside the target area. A pity.

In the final round, t-bots scored 510 points, while the winner scored 504. There is to say that, due to the hang of the network interface on my laptop (couldn’t ping the server…) g 3 of the 5 robots, two robots lose control, and just stopped working. Strangely, the third robot running on my machine continued to work… I’m really curios to know what could have happened from the log files stored by the organizers.

Others teams was featuring more complex strategies than t-bots (in my opinion), but maybe due to such complexity, most of them failed in having an effective mobility control. One of the features that was more impressing and interesting has been the mapping of the environment to detect visited areas, in order to optimize the search of the goal.


For working on t-bots I used the following tools:

My “ideal” robot

Looking at t-bots compared with other teams I saw during the competition, I elaborated some ideas (guidelines?) for my “perfect” robot: