Real-time environmental analysis for industrial vehicles based on synthetic sensor data and deep learning

Industrial vehicles often operate in the same environment as employees do. Monitoring their environment in real-time is essential to prevent accidents and injuries to employees. Machine learning methods are well-suited for people detection, but they require large amounts of training data. This article describes a real-time environmental analysis system based on 3D time-of-flight sensors and Deep Learning methods. Automatically labeled synthetic data as well as publically available real-world data were used for training. An in-situ evaluation was carried out on a real forklift truck in a warehouse. The results show that inexpensive and quickly generated synthetic data increases the robustness of environmental analysis.