[Article] Dynamical Stability of Aeroplanes by Hunsaker J. C.

By Hunsaker J. C.

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The # of UAVs with the smallest cost is then selected as that corresponding to the optimal setting. As previously discussed, the human is modeled as a server in a priority queuing system that services events generated by the UAVs according to arrival priorities. The average arrival and Model of Human Number_of_UAVs Mission Description Optimizer Vehicle Attributes Fig. 10. Optimization Model Prediction Predicting Operator Capacity for Supervisory Control of Multiple UAVs 29 Table 2. 31 service rates as well as their corresponding probabilistic distributions are as assumed earlier.

15] present a task allocation algorithm for multiple UAVs performing search, identification, attack, and verification tasks in an unknown region for targets that move in real time. These authors also address the problem of obstacle avoidance. Jin et al. [16] propose a probabilistic task allocation scheme for the scenario presented in [9, 1]. Recently, market based approaches have shown a considerable increase in performance for task allocation strategies to multiple agent applications. Dias and Stenz [17, 18] introduce a novel approach for coordinating robots based on the free market architecture in economics.

15. G. Osga, K. Van Orden, N. Campbell, D. Kellmeyer, and D. Lulue, “Design and Evaluation of WarfighterTask Support Methods in a Multi-Modal Watchstation,” SPAWAR, San Diego 1874, 2002. 16. L. J. Mitchell, “Automated Scheduling Decision Support for Supervisory Control of Multiple UAVs,” Journal of Aerospace Computing, Information, and Communication, in press. 17. B. G. A. Byrne, and R. Parasuraman, “The Effect of Adaptive Air Traffic Control (ATC) Decision Aiding on Controller Mental Workload,” in Human-automation Interaction: Research and Practice.

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