Last modified 3 years ago Last modified on 11/04/18 16:34:44

Lab Course: Robust Planning and Execution for Logistics Robots - Winter Term 2017/2018 The goal of this lab course is to develop an execution monitoring system that is able to cope with unexpected events, errors, and exogenous changes during the execution of a plan.


  • Till Hofmann
  • Tim Niemueller
  • Stefan Schiffer


The Knowledge Based Systems Group has implemented an autonomous agent competing in the RoboCup Logistics League as part of the Carologistics RoboCup Team. In our specific case a rule set describes a "production game" where robots must operate production lines. The CLIPS-based agent is implemented using the rule-based reasoning system CLIPS. Other agent implementations exist, e.g., all the agents competing in the Planning and Execution Competition for Logistics Robots in Simulation and [last year's ActorSim agent.

One common idea of all those agent systems is to compute a strategy (or plan) that consists of simple actions that are executed on the robots. Currently, most agents expect actions to always succeed and can only deal with some very specific exogenous events. In order to deal with failing actions (e.g., a failed pick-up action), other exogenous events (e.g., another robot blocking a machine), and changing goals (e.g., a new order), the agents have to do some kind of execution monitoring, which reacts to these events during execution and adapts the current plan accordingly.

The goal of this lab course is to design a monitoring system that can detect (simulated) events and react to them accordingly.

The basis for the lab course will be our 3D environment simulation for the RoboCup Logistics League. We want the participants' planning systems to compete against each other and the existing agent. Over the duration of the lab course, we will add more and more error sources to the simulation. We are interested to learn about different monitoring strategies that cope with these errors.

If you want to test things right now you can use our software release for 2015.


Simulation Competition

Planning and Execution Competition -- Rules and integration
This contains the rules for the competition. But more importantly, it contains the full documentation for the available PDDL actions (cf. Part II).


This section contains references that describe the systems that drive our robots and simulation.

Design Principles of the Component-Based Robot Software Framework Fawkes
(Tim Niemueller, Alexander Ferrein, Daniel Beck, Gerhard Lakemeyer; SIMPAR 2010)
Overview of the robot software framework Fawkes.
A Lua-based Behavior Engine for Controlling the Humanoid Robot Nao
(Tim Niemueller, Alexander Ferrein, Gerhard Lakemeyer; RoboCup Symposium 2009)
Paper about the Lua-based Behavior Engine, the mid-level reactive behavior layer that the agent instructs for skill execution.
Incremental Task-level Reasoning in a Competitive Factory Automation Scenario
(Tim Niemueller, Gerhard Lakemeyer, Alexander Ferrein; AAAI Spring Symposium 2013)
Description of the infrastructure used for the CLIPS-based agent.
Simulation for the RoboCup Logistics League with Real-World Environment Agency and Multi-level Abstraction
(Frederik Zwilling, Tim Niemueller, Gerhard Lakemeyer; RoboCup Symposium 2014)
Overview and principles of the Gazebo-based simulation for the RoboCup Logistics League.
The Carologistics RoboCup Logistics Team 2014
(Tim Niemueller, Sebastian Reuter, Daniel Ewert, Alexander Ferrein, Sabina Jeschke, Gerhard Lakemeyer; RoboCup 2014)
Description of the major features of the Carologistics RoboCup Team's robot systems.

Multi-robot systems (MRS) and RoboCup Logistics League (RCLL)

General literature relevant for multi-robot systems.

An Introduction to MultiAgent Systems
(Michael Wooldridge; 2002)
Basic introduction and consideration for multi-agent systems.
The RoboCup Logistics League as a Benchmark for Planning in Robotics
(Tim Niemueller, Gerhard Lakemeyer, Alexander Ferrein; 2015)
Characterization of the RCLL as a planning domain and explanation of terminology, e.g. local vs. global scope.
RoboCup Logistics League Sponsored by Festo: A Competitive Factory Automation Testbed
(Tim Niemueller, Daniel Ewert, Sebastian Reuter, Alexander Ferrein, Sabina Jeschke, Gerhard Lakemeyer; RoboCup Symposium 2013)
Description of the RoboCup Logistics League, covers the basics and game-specifics of 2013.
Proposal for Advancements to the LLSF in 2014 and beyond
(Tim Niemueller, Gerhard Lakemeyer, Alexander Ferrein, Sebastian Reuter, Daniel Ewert, Sabina Jeschke, Dirk Pensky, Ulrich Karras; WDRL at ICAR 2013)
Description of the changes in the LLSF in 2014 and in part 2014.
RoboCup Logistics League - Rules and Regulations 2015
(RoboCup Logistics League Technical Committee)
The rules of the RoboCup Logistics League as played in 2015.

Lecture Videos on RCLL, Fawkes, and CLIPS

RCLL Winter School 2015

Planning and Reasoning

Papers on planning and reasoning systems.

PDDL - The Planning Domain Definition Language
(Malik Ghallab, Craig Knoblock, Drew McDermott, Ashwin Ram, Manuela Veloso, Daniel Weld, David Wilkins; 1998)
Technical report on PDDL that defines the language and its syntax.
CLIPS Reference Manual
Programming Guide on the rule-based production system CLIPS.

Meetings and Milestones