Scheduling for humans in multirobot supervisory control

Sandra Mau, John Dolan
2007 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems  
This paper describes efficient utilization of human time by two means: prioritization of human tasks and maximizing multirobot team size. We propose an efficient scheduling algorithm for multirobot supervisory control that helps complete a mission faster. The proposed algorithm is superior to existing algorithms by prioritizing human tasks such that robots can regain autonomous control sooner. In simulations of a multirobot area surveying problem, we show that the rate of area coverage is much
more » ... igher using our algorithm compared to first-in-first-out. We also show that the use of different scheduling algorithms can affect the maximum number of robots a human can manage on a team. Another significant finding related to maximum team size is that the size is always the same or higher than an often-cited estimate known as fan-out [5]. Since fan-out is derived from an ideal, average case, simulations show that the upper bound on team size is higher than that predicted by the fan-out equation. Fan-out is actually a lower bound on the maximum team size for any practical situation (i.e., where task lengths and periodicity may vary or when robots are heterogeneous).
doi:10.1109/iros.2007.4399340 dblp:conf/iros/MauD07 fatcat:waopliknbnehxg5vze3dpaqouu