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Faculty of Electrical Engineering and Information Technology

Robot-assisted environment observation and documentation

Model predictive motion planning for robotic recording of human activities.

Today, a wide variety of application domains require authentic data of human activities and the associated changes to the environment to enable new data-based approaches to imitation or action recognition. However, recording highly specific activities is complex and costly. A robotic observation of the environmental state and recording of the activity offers an economical alternative.

To achieve this objective, model predictive motion planning for a collaborative robot with camera is developed considering the following aspects:

  • Predictive avoidance of collisions with humans to be observed in the workspace.
  • Real-time capable modeling of the environment and maximization of information gain through optimal camera movement
  • Seamless recording of the activity through proactive avoidance of occlusions
Comparison of a static collision avoidance (a) and a predictive collision avoidance (b).

We gratefully acknowledge the financial support of the project by the German Research Foundation (DFG, project number 497071854).