Frameworks and technologies for the monitoring, analysis and online adaption of industrial robotic production processes

ZIM, 2017 – 2018

Over the course of MonRob, three core technologies for the intuitive analysis and data-driven optimization of robot programs were developed.

  • Database and web-based user interface to collect and persist semantically annotated pose, joint, force-torque and meta-information from robot programs natively executed on the robot controller
  • 2D and 3D visualization solutions for the monitoring and analysis (clustering, statistical methods) of robot data
  • Deep learning-based robot program self-optimization: Prediction of object features with deep recurrent neural networks (RNNs), and online optimization of the robot program based on the predictions
  • Deep learning-based multimodal anomaly detection: Detection of anomalies in assembly processes with deep autoencoders on vision and force-torque data

MonRob laid the foundations of ArtiMinds Learning and Analytics for Robots (LAR), our commercial solution for powerful monitoring, analysis and optimization of robotic production processes.