Lab Course: Flexible Task-Level Reasoning and Execution for Logistics Robots

Submitted by tim on 12. July 2018 - 19:25
RCLL RoboCup 2015 (Hefei, China)

The Knowledge-Based Systems Group is, amongst others, doing research in task-level reasoning and agent controllers for mobile robots like in the RoboCup Logistics League (RCLL) as part of the Carologistics RoboCup Team.

Developing agents for such robotic tasks poses diverse problems to solve: acting rationally under hard real-time constraints, agent-to-agent communication, multi-robot cooperation, and task-level reasoning.

The goal of this lab course is to model the RCLL scenario and integrate a task planning system using existing planning tools and frameworks. Two frameworks to consider are PLEXIL (Plan Execution Interchange Language) and the respective executive (interpreter and execution program), as well as the CLIPS-based Executive (CX). Other approaches involve, for example, the Planning Domain Definition Language (PDDL). It has several variants and fragments with varying expressiveness and complexity.

The scenario for the lab course will be the RoboCup Logistics League (RCLL). In this scenario (top picture), two competing groups of three robots each must complete dynamic production chains according to orders which are posted throughout the game period of 15 minutes. We have developed a simulation of the RCLL (lower picture) that allows to quickly run the game and test without long setup times of real robots. This simulation is also the basis for the Planning and Execution Competition for Logistics Robots in Simulation.

RCLL 2016 Simulator Screenshot

In this lab course you have the chance to

  • learn about robot software development
  • develop an intelligent control program
  • apply methods of AI to robotic scenarios


The following shows a video of the simulation explaining its basic elements.

You can find many more videos showing and explaining the game at the Carologistics Youtube Channel. It specifically contains a playlist with videos of the RCLL Winter School 2015 that explain major components of the system.


  • basic study period completed (Bachelor/Vordiplom)
  • lecture "Artificial Intelligence" from our department
        (or objective evidence of equivalent knowledge)
  • programming skills (mostly C++)
  • interest in logic-based programming
  • high motivation
  • Linux skills beneficial


To be announced.


The rough outline of the lab course's schedule is as follows:

  • getting to know our software framework (Fawkes)
  • work in groups (2-4 students each)
  • concept + design
  • implementation
  • integration
  • evaluation

The date and time for the introductory meeting will be determined after the registration.