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AdViC-e: Advanced vision Control

General purpose: This project targets reliable vision-based chemical process control in adverse environmental and/or extreme plant conditions. In particular, a trustworthy and safe transition strategy from current human operator-based control to autonomous vision-based control is required. Concrete objectives: 1. Outdoor sensing and sensing in extreme conditions 2. Sensor fusion, anomaly detection (AD) and volume estimation 3. Vision-based process control with gradual transition from operator-based to fully autonomous control

Date:28 Jan 2021  →  Today
Keywords:Computer vision, Machine learning, Process control
Disciplines:Computer vision, Pattern recognition and neural networks, Machine learning and decision making
Project type:PhD project