Developing a complete robotic system often requires combining multiple behaviours into a complex decision grid, with elements running in sequence or in parallel, eventually interrupting each others. To solve this “age-old” problem, ROS provides two main tools: Actionlib: a client-server architecture that provides a way to specify results to be achieved. While the server works on these results, it should report progresses and ultimately report when the task is completed. Smach: a python API to define complex state machines. It can interact with ROS services and actions to define a complex behaviour, including nesting, interruptions and concurrence. Combining Smach and Actionlib, one could build arbitrarily complex systems. Hence, why would another task management system be necessary? The main argument in favour of our task scheduler is the simplicity of its use, particularly in comparison with Actionlib. As usual, simplicity is a trade-off against expressiveness. Simplicity can be sacrificed by linking our task scheduler with Actionlib and/or Smach to exploit the best of both worlds. This task scheduling framework is the culmination of about 10 years of experience developing robotic applications in the academic context. Most applications we designed could be handled using the task scheduling framework we will present in this document.