The authors present an overview of a hierarchical framework for coordinating task- and motion-level operations in multirobot systems. Their framework is based on the idea of using simple temporal networks to simultaneously reason about precedence/causal constraints required for task-level coordination and simple temporal constraints required to take some kinematic constraints of robots into account. In the plan-generation phase, the framework provides a computationally scalable method for generating plans that achieve high-level tasks for groups of robots and take some of their kinematic constraints into account. In the plan-execution phase, the framework provides a method for absorbing an imperfect plan execution to avoid time-consuming re-planning in many cases. The authors use the multirobot path-planning problem as a case study to present the key ideas behind their framework for the long-term autonomy of multirobot systems.
@article{arxiv.1804.00038,
title = {Overview: A Hierarchical Framework for Plan Generation and Execution in Multi-Robot Systems},
author = {Hang Ma and Wolfgang Hönig and Liron Cohen and Tansel Uras and Hong Xu and T. K. Satish Kumar and Nora Ayanian and Sven Koenig},
journal= {arXiv preprint arXiv:1804.00038},
year = {2018}
}