Most applications require subgroups of robots to perform different tasks. To support this, we designed a set of four distributed algorithms for dynamic task assignment. Given an input of desired task ratios, each robot selects a task such that the final global distribution best matches the input distribution. Although all four algorithms have the same final goal, each of them represents different trade-offs in running time, communications usage, and accuracy of the final result. These trade-offs were interesting, and pointed towards a model of conserved quantities in multi-robot computation.
Current Researchers: James McLurkin
Project Status: Active