In urban search and rescue (USAR) missions, manually controlling robots is difficult, in large part due to low situation awareness (SA) provided by operator control units (OCUs). This paper looks at state-of-the-art OCUs to identify seven fundamental problems to be resolved. Next, the design and implementation of a multi-view multi-modal OCU are presented. This OCU follows a large set of design guidlines and also features novel techniques for a human operator to remotely interact with a man-portable ground robot. The system was evaluated in a high fidelity tunnel accident simulation at a fire fighting training center. The OCU allowed training and collisions to remain low, while SA was improved. Qualitative observations are also discussed, such that end-users do not often choose the optimal views in the OCU for the tasks at hand.
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