# Should we get involved? impact of human collaboration and intervention on multi-robot teams

## TL;DR

This paper studies how human involvement affects the performance of multi-robot teams through simulation, showing that more robots and collaboration improve efficiency.

## Contribution

A simulation framework for human-in-the-loop multi-robot teams using JADE, analyzing the impact of human collaboration and intervention.

## Key findings

- Task execution and request completion times improve with more robots in the team.
- Human collaboration reduces request completion time, while human intervention increases it.
- System architecture only significantly affects performance when the number of robots is low.

## Abstract

The challenges encountered in the design of multi-robot teams (MRT) highlight the need for different levels of human involvement, creating human-in-the-loop multi-robot teams. By integrating human cognitive abilities with the functionalities of the robots in the MRT, we can enhance overall system performance. Designing such a human-in-the-loop MRT requires several decisions based on the specific context of application. Before implementing these systems in real-world scenarios, it is essential to model and simulate the various components of the MRT to evaluate their impact on performance and the different roles a human operator might play.

We developed a simulation framework for a human-in-the-loop MRT using the Java Agent DEvelopment framework (JADE) and investigated the effects of different numbers of robots in the MRT, MRT architectures, and levels of human involvement (human collaboration and human intervention) on performance metrics.

Results show that task execution outcomes and request completion times (RCT) improve with an increasing number of robots in the MRT. Human collaboration reduced the RCT, while human intervention increased the RCT, regardless of the number of robots in the MRT. The effect of system architecture was only significant when the number of robots in the MRT was low.

This study demonstrates that both the number of robots in a multi-robot team (MRT) and the inclusion of a human in the loop significantly influence system performance. The findings also highlight the value of simulation as a cost- and time-efficiency strategy to evaluate MRT configurations prior to real-world implementation.