This paper describes the initial steps in the development of an object detection system for manipulation purposes, to be embedded in a mobile robot. The goal is to design a robotic system to aid workers in a manufacturing plant. The proposed implementation involves the integration of a Field Programmable Gate Array (FPGA) based electronic module with the manipulator arm of the robotic platform. The whole system is provided with a camera which captures images of the objects that can be found in the environment. The FPGA performs the object recognition tasks by means of a neural network. Additional image processing algorithms are used to convert the images obtained by the camera into useful information for the neural network.

This paper describes the development of a FPGAbased 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.