Algorithms for dynamic switching of collaborative human-robot system in target recognition tasks

This paper presents a set of algorithms developed for real-time dynamic switching between collaboration levels in a human-robot target recognition system. The algorithms were developed for a closed-loop controller to maximize system performance despite deviations in the parameter values and were evaluated by conducting a thorough simulation analysis. These developments enable smooth realtime adaptation of the combined human-robot system to many possible changes of the environment, human operator and robot performance. System performance was analyzed in simulations for a variety of target probabilities distributions. Improvements that can be achieved by each algorithm were calculated as a mean value for 200 independent simulations for each target probability distribution. The numerical analysis results indicated that the developed algorithms for dynamic switching achieved improved system performance.