Proactive Model for Handling Conflicts in Sensor Data Fusion Applied to Robotic Systems

Abstract

Robots have to be able to function in a multitude of different situations and environments. To help them achieve this, they are usually equipped with a large set of sensors whose data will be used in order to make decisions. However, the sensors can malfunction, be influenced by noise or simply be imprecise. Existing sensor fusion techniques can be used in order to overcome some of these problems, but we believe that data can be improved further by computing context information and using a proactive rule-based system to detect potentially conflicting data coming from different sensors. In this paper we will present the architecture and scenarios for a generic model taking context into account.

Separation of Concerns Within Robotic Systems Through Proactive Computing

“…The main motivation is to provide a system that can proactively determine our needs and dynamically act. Thus, allowing the PS to act for and on behalf of the user on their own initiative [2,3,7], excluding them from the "loop". The main advantage of this transition is faster computation time, because computers will handle decision making themselves.…”