This paper proposes a novel dynamic method based on Behavior Trees (BTs) that integrates planning and allocation of tasks in mixed human robot teams, suitable for manufacturing environments. The Behavior Tree formulation allows encoding a single job as a compound of different tasks with temporal and logic constraints. In this way, instead of formulating an offline centralized optimization problem, the role allocation problem is solved with multiple simplified online optimization sub-problems, without complex and cross-schedule task dependencies. These sub-problems are defined as Mixed-Integer Linear Programs (MILPs), that, according to the worker-actions related costs and the workers' availability, allocate the yet-to-execute tasks among the available workers. To characterize the behavior of the developed method, we opted to perform different simulation experiments, in which the results of the action-worker allocation and the computational complexity are evaluated. The obtained results, due to the nature of the algorithm and to the possibility of simulating the agents' behavior, illustrate adequately also how the algorithm performs in real experiments.

An integrated dynamic method for allocating roles and planning tasks for mixed human-robot teams

Fusaro F.;De Momi E.;Ajoudani A.
2021-01-01

Abstract

This paper proposes a novel dynamic method based on Behavior Trees (BTs) that integrates planning and allocation of tasks in mixed human robot teams, suitable for manufacturing environments. The Behavior Tree formulation allows encoding a single job as a compound of different tasks with temporal and logic constraints. In this way, instead of formulating an offline centralized optimization problem, the role allocation problem is solved with multiple simplified online optimization sub-problems, without complex and cross-schedule task dependencies. These sub-problems are defined as Mixed-Integer Linear Programs (MILPs), that, according to the worker-actions related costs and the workers' availability, allocate the yet-to-execute tasks among the available workers. To characterize the behavior of the developed method, we opted to perform different simulation experiments, in which the results of the action-worker allocation and the computational complexity are evaluated. The obtained results, due to the nature of the algorithm and to the possibility of simulating the agents' behavior, illustrate adequately also how the algorithm performs in real experiments.
2021
2021 30th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2021
978-1-6654-0492-1
File in questo prodotto:
File Dimensione Formato  
An_Integrated_Dynamic_Method_for_Allocating_Roles_and_Planning_Tasks_for_Mixed_Human-Robot_Teams.pdf

Accesso riservato

: Publisher’s version
Dimensione 2.02 MB
Formato Adobe PDF
2.02 MB Adobe PDF   Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1203889
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 10
  • ???jsp.display-item.citation.isi??? 7
social impact