The deployment of industrial robotic cells based on lean manufacturing principles enables the development of fast-reconfigurable assembly lines in which human and robotic agents collaborate to achieve a shared task. To ensure the effective coordination of the shared effort, each task must be decomposed into a sequence of atomic actions that can be assigned either to a single agent or to the combination of more agents, according to a defined metric. While task allocation is a general problem and has been discussed intensively in other fields, less effort has been devoted in industrial scenarios, involving mixed human-robot teams and in particular, to the factors that should be considered in allocating tasks among a heterogeneous set of agents in collaborative manufacturing scenarios. In this letter, we investigate the agent characteristics that should be considered in the task allocation problem of fast-reconfigurable systems in industrial assembly processes. First, we introduce a set of indices, namely task complexity, agent dexterity, and agent effort, to evaluate agent performance with respect to a task. Second, we propose an offline allocation algorithm that combines the performance indices to assign optimally the task to the team agents. Finally, we validate the framework in a proof-of-concept collaborative assembly of a metallic structure. The results show that the workload is shared through the agents according to their particular physical capabilities and skill levels. A subjective analysis of the proposed collaborative framework on 12 healthy participants also validated the intuitiveness-of-use and improved performance.

A Capability-Aware Role Allocation Approach to Industrial Assembly Tasks / Lamon, Edoardo; De Franco, Alessandro; Peternel, Luka; Ajoudani, Arash. - In: IEEE ROBOTICS AND AUTOMATION LETTERS. - ISSN 2377-3766. - 4:4(2019), pp. 3378-3385. [10.1109/LRA.2019.2926963]

A Capability-Aware Role Allocation Approach to Industrial Assembly Tasks

Lamon, Edoardo
Primo
;
2019-01-01

Abstract

The deployment of industrial robotic cells based on lean manufacturing principles enables the development of fast-reconfigurable assembly lines in which human and robotic agents collaborate to achieve a shared task. To ensure the effective coordination of the shared effort, each task must be decomposed into a sequence of atomic actions that can be assigned either to a single agent or to the combination of more agents, according to a defined metric. While task allocation is a general problem and has been discussed intensively in other fields, less effort has been devoted in industrial scenarios, involving mixed human-robot teams and in particular, to the factors that should be considered in allocating tasks among a heterogeneous set of agents in collaborative manufacturing scenarios. In this letter, we investigate the agent characteristics that should be considered in the task allocation problem of fast-reconfigurable systems in industrial assembly processes. First, we introduce a set of indices, namely task complexity, agent dexterity, and agent effort, to evaluate agent performance with respect to a task. Second, we propose an offline allocation algorithm that combines the performance indices to assign optimally the task to the team agents. Finally, we validate the framework in a proof-of-concept collaborative assembly of a metallic structure. The results show that the workload is shared through the agents according to their particular physical capabilities and skill levels. A subjective analysis of the proposed collaborative framework on 12 healthy participants also validated the intuitiveness-of-use and improved performance.
2019
4
Lamon, Edoardo; De Franco, Alessandro; Peternel, Luka; Ajoudani, Arash
A Capability-Aware Role Allocation Approach to Industrial Assembly Tasks / Lamon, Edoardo; De Franco, Alessandro; Peternel, Luka; Ajoudani, Arash. - In: IEEE ROBOTICS AND AUTOMATION LETTERS. - ISSN 2377-3766. - 4:4(2019), pp. 3378-3385. [10.1109/LRA.2019.2926963]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/378949
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