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A capability-aware role allocation approach to industrial assembly tasks
- Source :
- IEEE Robotics and Automation Letters, 4(4)
- Publication Year :
- 2019
-
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.
- Subjects :
- assembly
0209 industrial biotechnology
Control and Optimization
Computer science
Biomedical Engineering
02 engineering and technology
Lean manufacturing
Task (project management)
020901 industrial engineering & automation
Artificial Intelligence
Human–computer interaction
0202 electrical engineering, electronic engineering, information engineering
Set (psychology)
Structure (mathematical logic)
Sequence
Physical human-robot interaction
Mechanical Engineering
020208 electrical & electronic engineering
Physical human-robot interaction,assembly,intelligent and flexible manufacturing,task planning
Workload
Computer Science Applications
Human-Computer Interaction
Control and Systems Engineering
Software deployment
intelligent and flexible manufacturing
Metric (mathematics)
Computer Vision and Pattern Recognition
task planning
Subjects
Details
- Language :
- English
- ISSN :
- 23773766
- Database :
- OpenAIRE
- Journal :
- IEEE Robotics and Automation Letters, 4(4)
- Accession number :
- edsair.doi.dedup.....aed6bf7e0e9dc3e0d5b77c7b62d40cbc