The present dissertation aims at implementing a C++ real time human trajectory predictor for autonomous mobile robots in indoor unstructured environments. The main objectives of the prediction system are the optimization of the robot path planning process and the improvement of the robot ability to safely coexist with the surrounding human beings. To make the robot aware of the future behaviour of the people, the proposed software package first generates a prediction taking into account the human-human, the human-scene and the human-robot interactions and then makes the obtained information available to the robot planner by inserting proper cost areas into those locations of the navigation costmap that are believed to be crossed by the pedestrians over the next 2.4 s; thanks to these additional costs, the robot is induced to avoid the crossed areas, and no trajectory superposition takes place.