posted on 2006-01-01, 00:00authored byE. Gil Jones, Brett Browning, M. Bernardine Dias, Brenna Argall, Manuela M. Veloso, Anthony Stentz
As we progress towards a world where robots play
an integral role in society, a critical problem that remains to be
solved is the Pickup Team Challenge; that is, dynamically formed
heterogeneous robot teams executing coordinated tasks where
little information is known a priori about the tasks, the robots,
and the environments in which they will operate. Successful
solutions to forming pickup teams will enable researchers to
experiment with larger numbers of robots and enable industry
to efficiently and cost-effectively integrate new robot technology
with existing legacy teams. In this paper, we define the challenge
of pickup teams and propose the treasure hunt domain for
evaluating the performance of pickup teams. Additionally, we
describe a basic implementation of a pickup team that can search
and discover treasure in a previously unknown environment. We
build on prior approaches in market-based task allocation and
plays for synchronized task execution, to allocate roles amongst
robots in the pickup team, and to execute synchronized team
actions to accomplish the treasure hunt task.