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asr_ros_pkgs is a software framework which impements the approach 'Active Scene Recognition (ASR)' and has been developed at the Chair of Prof. Dr.-Ing. R. Dillmann, Humanoids and Intelligence Systems Lab (HIS), Karlsruhe Institute of Techology (KIT), Germany. ASR is an approach for mobile robots to recognize scenes in distributed and cluttered indoor environments. It combines scene recognition and object search: Information about partially recognized scenes is used to guide the subsequent search for missing objects. In implementing ASR, asr_ros_pkgs provides both

The scene classifier can be used independently of ASR for what we call Passive Scene Recognition (PSR). As PSR, we define scene recognition with an immobile observer.

This project is of use for any researcher who intends to estimate the state of a robot's environment based on both the objects present in the environment and the 6-D spatial relations between the objects. Such estimates can be used for robotic decision-making, e.g., in the context of action planning.

As a starting point for


The research project 'Learning the Context in Programming by Demonstration of Manipulation Tasks', during the course of which asr_ros_pkgs was created, has been a 3-year research grant funded by the German Research Foundation (DFG).











Further information on our research is available unter www.sceneexploration.org. We are happy to provide supplementary information and to improve this documentation. So please feel free to reach out to us through asr-ros AT lists DOT kit DOT edu if anything remains unclear after having read it.

When using Active Scene Recognition, please cite our 'International Conference on Robotics and Automation, 2014' paper. Thank you!

2020-01-18 12:28