Impact of two Adjustable Autonomy Models 1 TOPIC CHOICE: Automation, Expert Systems IMPACT OF TWO ADJUSTABLE AUTONOMY MODELS ON THE SCALABILITY OF SINGLE-HUMAN-MULTIPLE-ROBOT TEAMS FOR EXPLORATION MISSIONS

Objective: Evaluate two models for adjusting autonomy in mobile robots, seeking to find out what is the best way for the operator to interact with the system with as many robots as possible. The first model is the most used in mobile robots, the second proposes a flexible autonomy management. Background: There are different ways of adjusting the autonomy level in man-machine systems: “Adjustable autonomy”, in which the operator has the initiative over the autonomy level, “adaptive autonomy”, in which the autonomy level is adjusted depending on the task and context, and “mixed initiatives”. One of the drawbacks of using adjustable autonomy is that it is claimed not to be flexible enough, resulting in a high operator workload. We propose and evaluate a flexible adjustable autonomy model for robot-team supervision. Method: Two experiments were designed to test the scalability and performance of the manmachine system with two alternative configurations for the autonomy management. The independent variable is the number of robots, while the measured variable is the manmachine system performance. The experiments are between-subjects. We have used ANOVA and Bonferroni post-hoc analysis for analyzing the results. Results: On the basis of these analyses, we conclude that a flexible adjustable autonomy model drives to better performance than the classic, rigid one, in which the operator directly chooses the autonomy level. Conclusion: Flexible autonomy adjustment permits one operator to control a team of robots with better results in terms of performance and robot utilization, as he can directly act at the error level, leaving the responsibility of re-adjusting and resuming the task to the system and hence reducing the operator's workload. Impact of two Adjustable Autonomy Models 4 Application: Exploration robotics, mainly, with one operator controlling a team of robots. In general, these principles can be extended to other single-man-multiple-machine systems. Address correspondence to Alberto Valero-Gomez, Universidad Carlos III de Madrid, Av. Universidad, 30. 28911, Leganés (Madrid).SPAIN; [email protected].