Goal Reasoning in the CLIPS Executive for Integrated Planning and Execution

The close integration of planning and execution is a challenging problem. Key questions are how to organize and explicitly represent the program flow to enable reasoning about it, how to dynamically create goals from run-time information and decide on-line which to pursue, and how to unify representations used during planning and execution.In this work, we present an integrated system that uses a goal reasoning model which represents this flow and supports dynamic goal generation. With an explicit world model representation, it enables reasoning about the current state of the world, the progress of the execution flow, and what goals should be pursued – or postponed or abandoned. Our executive implements a specific goal lifecycle with compound goal types that combine sub-goals by conjunctions, disjunctions, concurrency, or that impose temporal constraints.Goals also provide a frame of reference for execution monitoring. The current system can utilize PDDL as the underlying modeling language with extensions to aid execution, and it contains well-defined extension points for domain-specific code. It has been used successfully in several scenarios

Integrated Synthesis and Execution of Optimal Plans for Multi-Robot Systems in Logistics

Model-based synthesis allows to generate plans to achieve high-level tasks while satisfying certain properties of interest. However, when such plans are executed on concrete systems, several modeling assumptions may be challenged, jeopardizing their real applicability. This paper presents an integrated system for generating, executing and monitoring optimal-by-construction plans for multi-robot systems. This system unites the power of Optimization Modulo Theories with the flexibility of an on-line executive, providing optimal solutions for high-level task planning, and runtime feedback on their feasibility. After presenting how our system orchestrates static and runtime components, we demonstrate its capabilities using the RoboCup Logistics League as testbed. We do not only present our final solution but also its chronological development, and draw some general observations for the development of OMT-based approaches

On the synthesis of guaranteed-quality plans for robot fleets in logistics scenarios via optimization modulo theories

In manufacturing, the increasing involvement of autonomous robots in production processes poses new challenges on the production management. In this paper we report on the usage of Optimization Modulo Theories (OMT) to solve certain multi-robot scheduling problems in this area. Whereas currently existing methods are heuristic, our approach guarantees optimality for the computed solution. We do not only present our final method but also its chronological development, and draw some general observations for the development of OMT-based approaches

BendIT – An Interactive Game with two Robots

Abstract. In this paper we report on an interactive game with two robots and review its components. A human user uses his torso movements to steer a Robotino robot along a pre-defined course. Our domestic service robot Caesar acts as a referee and autonomously follows the Robotino and makes sure that it stays within a corridor along the path. If the user manages to keep the Robotino within the corridor for the whole path he wins. The game can be used, for example, to engage people in physical training such as a rehabilitation after an injury. It was designed and implemented as a student project in winter term 2011/2012.