Performance Analysis and Modelling of Future Integrated Human-Robotic Space Operations

Abstract

Pioneering work reinvents the parameters of the possible, and violates the laws of the impossible. Though space exploration is an expanding topic, the future missions to the Moon are the firsts to have humans and automated systems working together to explore new terrains. Preparing the future of human-robotic integrated space operations is a stepping stone for lunar missions, and the current study aims to lead the way towards the next giant leap for mankind. While many studies and experiments focus on the realisation and feasibility of human-robotic activities for space applications, there is a gap in knowledge when it comes to the direct preparation of such operations for near-future lunar missions. In order to prepare such activities the performance of both human and system must be assessed, and this requires either regular highly expensive experiments to obtain performance data, or an innovative and lean assessment approach. The proposed method is the performance analysis and modelling of future integrated human-robotic space operations, using existing data from experiments conducted aboard the International Space Station in which a crew member controls a rover located on Earth. This situation creates the ideal scenario for an analogue experiment above and beyond its original objective. By gathering such experiment data and performing a time analysis of the performance, time estimations are made for a set of tasks and the results can be applied to various scenarios of operations without the skyrocketing cost and crew time. The results of this method demonstrated that it is possible to analyse the time of previous experiments to gain insight on the command time of the human operator and the execution time of the system and that a preliminary tool can be developed to assess the command time and execution time for future operations, based on obtained data from previous experiments. Using the time averages of the data from previous experiments, the gaps are filled of data that was not recorded or incorrectly recorded due to error, under the conditions of the assumption. Expanding on this outcome, it can be implemented to simulate mission specific conditions and results. Using existing parameters, this analysis holds potential to pave the way for the future of experiment preparations such that they in turn prepare the road for future missions to the lunar surface.