  In this letter, an integrated task planning and reactive motion planning
framework termed Multi-FLEX is presented that targets real-world, industrial
multi-robot applications. Reactive motion planning has been attractive for the
purposes of collision avoidance, particularly when there are sources of
uncertainty and variation. Most industrial applications, though, typically
require parts of motion to be at least partially non-reactive in order to
achieve functional objectives. Multi-FLEX resolves this dissonance and enables
such applications to take advantage of reactive motion planning. The Multi-FLEX
framework achieves 1) coordination of motion requests to resolve task-level
conflicts and overlaps, 2) incorporation of application-specific task
constraints into online motion planning using the new concepts of task
dependency accommodation, task decomposition, and task bundling, and 3) online
generation of robot trajectories using a custom, online reactive motion
planner. This planner combines fast-to-create, sparse dynamic roadmaps (to find
a complete path to the goal) with fast-to-execute, short-horizon, online,
optimization-based local planning (for collision avoidance and high
performance). To demonstrate, we use two six-degree-of-freedom, high-speed
industrial robots in a deburring application to show the ability of this
approach to not just handle collision avoidance and task variations, but to
also achieve industrial applications.
