Fatigue-Aware Sub-Second Combinatorial Auctions for Dynamic Cycle Allocation in Human–Robot Collaborative Assembly

Claudio Urrea ()
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Claudio Urrea: Electrical Engineering Department, Faculty of Engineering, University of Santiago of Chile, Las Sophoras 165, Estación Central, Santiago 9170020, Chile

Mathematics, 2025, vol. 13, issue 15, 1-21

Abstract: Problem: Existing Human–Robot Collaboration (HRC) allocators cannot react at a sub-second scale while accounting for worker fatigue. Objective: We designed a fatigue-aware combinatorial auction executed every 100 ms. Method: A human and a FANUC robot submit bids combining execution time, predicted energy, and real-time fatigue; a greedy algorithm (≤1 ms) with a 1 − 1 / e approximation guarantee and O (| Bids | log | Bids |) complexity maximizes utility. Results: In 1000 RoboDK episodes, the framework increases active cycles·min −1 by 20%, improves robot utilization by +10.2 percentage points, reduces per cycle fatigue by 4%, and raises the collision-free rate to 99.85% versus a static baseline ( p < 0.001). Contribution: We provide the first transparent, sub-second, fatigue-aware allocation mechanism for Industry 5.0, with quantified privacy safeguards and a roadmap for physical deployment. Unlike prior auction-based or reinforcement learning approaches, our model uniquely integrates a sub-second ergonomic adaptation with a mathematically interpretable utility structure, ensuring both human-centered responsiveness and system-level transparency.

Keywords: human–robot collaboration; auction-based dynamic cycle allocation; combinatorial auctions; mathematical optimization; dynamic cycle assignment; industrial assembly; Industry 5.0 (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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