A likelihood analysis for a risk analysis for safe human robot collaboration

With the trend of increasing human robot collaboration, the need for more advanced safety systems arises. To create safe robots that act proactive to dangers, a safety system based on risk analysis has been developed. This paper presents a vital part of the risk analysis, the likelihood analysis,. In this likelihood analysis, data about human activity is recorded based on its occupied space. The times of an occupation are recorded in absolute and relative time. A multi-peak probability distribution is fitted to the data using a hidden genes genetic algorithm. This algorithm enabled the system to also optimize the number of peaks in the distribution. The system is implemented and simulated for a simple assembly task. Plots from the simulations show the system´s ability to predict active and inactive periods of time in a given area. This information can later be used in a risk analysis based scheduling problem.