# An Efficient Scheduling Algorithm for Multi-Robot Task Allocation in Assembling Aircraft Structures

## TL;DR

This paper introduces an efficient scheduling algorithm for multi-robot aircraft assembly that balances workloads, avoids collisions, and adapts to robot failures, significantly improving schedule efficiency with minimal computation time.

## Contribution

The paper presents a novel method combining geometry-based initial scheduling with market-based reallocation to handle robot failures efficiently.

## Key findings

- 11.5% improvement in schedule efficiency over greedy scheduler
- Schedules computed in hundreds of milliseconds
- Effective handling of robot failures in real-time

## Abstract

Efficient utilization of cooperating robots in the assembly of aircraft structures relies on balancing the workload of the robots and ensuring collision-free scheduling. We cast this problem as that of allocating a large number of repetitive assembly tasks, such as drilling holes and installing fasteners, among multiple robots. Such task allocation is often formulated as a Traveling Salesman Problem (TSP), which is NP-hard, implying that computing an exactly optimal solution is computationally prohibitive for real-world applications. The problem complexity is further exacerbated by intermittent robot failures necessitating real-time task reallocation. In this letter, we present an efficient method that exploits workpart geometry and problem structure to initially generate balanced and conflict-free robot schedules under nominal conditions. Subsequently, we deal with the failures by allowing the robots to first complete their nominal schedules and then employing a market-based optimizer to allocate the leftover tasks. Results show an improvement of 11.5\% in schedule efficiency as compared to an optimized greedy multi-agent scheduler on a four robot system, which is especially promising for aircraft assembly processes that take many hours to complete. Moreover, the computation times are similar and small, typically hundreds of milliseconds.