Development of an embedded system for visual servoing in an industrial scenario

This paper describes the development of a FPGA-based object detection algorithm for manipulation purposes in a mobile robot. The target application is a robotic system which aids workers in a manufacturing plant. The whole system is provided with a camera which captures images of the objects that can be found in the environment. The FPGA extracts the most useful data from these images and performs the object recognition tasks by means of a neural network. For performance reasons, the neural network is implemented in the hardware partition of the system, while the rest of the algorithms is included in an embedded processor. This design provides a tradeoff between the flexibility and accuracy of the software in performing image processing algorithms and the high-speed of the hardware to execute parallel computations, useful for the neural network.