A New Shopfloor Orchestration Approach for Collaborative Human-Robot Device Disassembly

We present a new approach to tackle the problem
of task assignment and scheduling in human-robot teams that
undertake collaborative device disassembly tasks. The proposed
approach is a hybrid between a global search metaheuristic
and an adaptive greedy operation assignment and scheduling
algorithm. We propose the concept of an Adaptive (work)Cell,
(aCell), which becomes the basis for the hierarchical organiza-
tion of the proposed search approach. At high level, metaheuris-
tic search establishes resource constraints for each aCell and de-
termines parameters for the task-level operation scheduling. At
low level, the task-level scheduling algorithm produces feasible
assignments and schedules within a single aCell by backtracking
through feasible time slots using an adaptive score metric. The
advantage of the proposed approach is that it clearly delineates
between higher level state space exploration and focused, task-
oriented exploitation. We validate the proposed approach on
a class of novel multi-objective benchmark problems involving
human-robot teams collaborating throughout a factory floor,
addressing specifically for the first time the problem of device
disassembly tasks, relevant to WEEE recycling, with additional
constraints, where we obtain favorable results.