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Autonomous Task Planning and Execution

Solving arbitrary manipulation tasks is a key feature for humanoid service robots. However, especially when tasks involve handling complex mechanisms or using tools, a generic action description is hard to define. Different objects require different handling methods. Therefore, a modular system architecture has been developed to autonomously solve manipulation tasks from the object point of view.

Functional Object Classes:

• Objects categorized by functionality in a hierarchical structure
• Description of generic process models on the symbolic and geometric level via action templates

Hybrid Reasoning based on Object Knowledge:

• An object storage provides prior object knowledge
• The current world state is used as initial state for the symbolic planner
• Action templates ground the symbolic planners outcome
• Individual robot components are addressed on the geometric level

Selected Publications

Daniel Leidner, Christoph Borst, and Gerd Hirzinger, "Things Are Made for What They Are: Solving Manipulation Tasks by Using Functional Object Classes", in Proc. of the IEEE-RAS International Conference on Humanoid Robots, Osaka, Japan, November 2012, pp. 429–435.