Learning patterns for complex event detection in robot sensor data

Abstract

We present an approach for learning patterns for Complex Event Processing (CEP) in robot sensor data. While the robot executes a certain task, sensor data is recorded. The sensor data recordings are classified in terms of events or outcomes that characterize the task. These classified recordings are then used to learn simple rules that describe the events using a simple, domain specific language, in a human-readable and interpretable way.