Sharing the Load in Mobile Robotic Networks

Equitable partition

The design of cooperative control policies for the robots has to typically address three key challenges: (i) task allocation among the robots, (ii) service scheduling for each robot, and (iii) design of loitering strategies, i.e., strategies to adopt for robots with no assigned tasks. In general, these challenges are coupled. Therefore, devising an optimal, or at least provably efficient policy is often a difficult problem.
A natural way to reduce the complexity is to partition the workspace among the robots and then let each robot follow a certain set of rules in its own region. To what extent does this decoupling strategy affect optimality? In collaboration with A. Arsie (U. of Toledo), E. Frazzoli (MIT), and F. Bullo (UCSB), Marco Pavone has:
  • characterized specific scenarios where one can retain optimality, or at least some degree of optimality, under this partitioning scheme, [Paper],
  • designed partitioning algorithms that do not require any centralized computation (an important property for robotic networks comprising several robots that operate in an unknown dynamic environment). The design and analysis of such algorithms require a variety of techniques from control theory, computational geometry and algebraic topology. Their application can be found here. [Paper]

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