An Artificial Protection Field Approach For Reactive Obstacle Avoidance in Mobile Robots

Abstract

In this work, we have presented a reactive obstacle avoidance approach based on a situatedactivity paradigm. Our system has demonstrated to be robust in qualitative tests developed on a dynamically changing environment. We have shown tests in a custom-developed simulation platform and in the real robot. Our approach is based in the risk assessment made by the robot by using an artificial protection field to avoid moving obstacles. In the near future, we will evaluate quantitative performance of the method by analyzing pose errors after the re-planning step both in simulation and in the real robotic platform XidooBot. Fusion of several sensors information will be done in order to improve the robustness of this approach. This method will be integrated with a topological navigation system.