Knowledge-Based Servoing

Knowledge-Based Servoing: Plugging Symbolic Theories into Robotic Controllers

This virtual research lab explores reactive motion generation through reasoning. We propose image schema-based reasoning for decision-making within motion controllers. Our reasoner is tightly coupled with the controller, continuously monitoring actions and inferring motion primitives to adapt to dynamic environments. The symbolic theory and the reasoner evaluating it can be exchanged in a plug and play way. By providing real-time feedback, the reasoner enables the controller to make informed decisions and generate appropriate motion responses.

Source Code

• Rule with semantic interpreter
• Giskard
• Reasoner
• Simulation

Publications

• Huerkamp, M.; Dhanabalachandran, K.; Pomarlan, M.; Stelter, S. and Beetz, M. (2025). A Modular Framework for Knowledge-Based Servoing: Plugging Symbolic Theories into Robotic Controllers. In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 1, ISBN 978-989-758-737-5, ISSN 2184-433X, pages 886-897.

• Mihai Pomarlan, Kaviya Dhanabalachandran, and Michael Beetz. Towards reactive robotics with a pinch of image-schematic reasoning. In ISD, 2023

Authors

• Malte Huerkamp
  Tel: +49 421 218 64020
  Email: huerkamp@uni-bremen.de
  Profile: https://ai.uni-bremen.de/team/malte_huerkamp/
• Kaviya Dhanabalachandran
  Tel: +49 421 218 64000
  Email: kaviya@cs.uni-bremen.de
  Profile: https://ai.uni-bremen.de/team/kaviya_dhanabalachandran
• Mihai Pomarlan
  Tel: +49 421 218 64421
  Email: mpomarlan@yahoo.co.uk
• Simon Stelter
  Tel: +49 421 218 64014
  Email: stelter@cs.uni-bremen.de
  Profile: https://ai.uni-bremen.de/team/simon_stelter
  
• Prof. Michael Beetz PhD
  Tel: +49 421 218 64001
  Email: beetz@cs.uni-bremen.de
  Profile:  https://ai.uni-bremen.de/team/michael_beetz