Communicating and negotiating among robots is challenging. We should ensure our robots address collision while they are moving. Meanwhile, these robots should achieve their goals collectively.

For example, Keisuke Uto has created a multi-robot implementation to create a specific formation. They take input from their cameras. Then, these robots arrange themselves to create a formation. To get the correct robot formation, this system uses a camera to detect the current robot formation. Each robot has been labelled so it makes the system able to identify the robot formation.

By implementing image processing, Keisuke shows how multiple robots create a formation using multi-robot cooperation. If you are interested, you can read about the project at https://www.digi.com/blog/xbee/multi-robot-formation-control-by-self-made-robots/. Here they are in action:

For another example, can have soccer matches in which the players are not human; they are all robots. Such a competition can use custom robots or existing commercial robots such as the Nao robot, https://www.ald.softbankrobotics.com/en/robots/nao. You can see Nao robots in a soccer match here:

As we know, a robot soccer game involves robots, and they need skill and knowledge in order to win. The robot should detect the ball and score goals. Meanwhile, each robot should perform group cooperation. Addressing collision among robots and passing the ball to its group are challenging in this area.