Task allocation using a team or coalition of robots is one of the most
important problems in robotics, computer science, operational research, and
artificial intelligence. In recent work, research has focused on handling
complex objectives and feasibility constraints amongst other variations of the
multi-robot task allocation problem. There are many examples of important
research progress in these directions. We present a general formulation of the
task allocation problem that generalizes several versions that are
well-studied. Our formulation includes the states of robots, tasks, and the
surrounding environment in which they operate. We describe how the problem can
vary depending on the feasibility constraints, objective functions, and the
level of dynamically changing information. In addition, we discuss existing
solution approaches for the problem including optimization-based approaches,
and market-based approaches.

本文介绍一个通用的、广泛涉及机器人、计算机科学、运筹学和人工智能等领域的任务分配问题，包括机器人、任务和周围环境状态的多个版本，并探讨了解决该问题的现有方法，包括基于优化和市场的方法。