In any field or operation, it is desirable to optimize the labor resources available such that multiple agents, both human and/or robot, can work on tasks in concert to maximize productivity. This resource integration must meet certain temporal and spatial constraints to support efficient and safe co-work. The multi-agent coordination problem with temporo-spatial constraints can be formulated as a mixed integer linear program (MILP). However, this approach is exponential in complexity and becomes computationally intractable for large-scale operations. The Inventors have developed Tercio, a new and efficient framework for real-time, near-optimal task scheduling that is scalable to large operations.