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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2508.03765 |
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| _version_ | 1866908529600757760 |
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| author | Dhar, Soumyadeep Saha, Ariyan Kumar |
| author_facet | Dhar, Soumyadeep Saha, Ariyan Kumar |
| contents | This paper investigates the critical role of trust and fatigue in human-cobot collaborative order picking, framing the challenge within the scope of Logistics 5.0: the implementation of human-robot symbiosis in smart logistics. We propose a dynamic, leader-follower Stackelberg game to model this interaction, where utility functions explicitly account for human fatigue and trust. Through agent-based simulations, we demonstrate that while a naive model leads to a "trust death spiral," a refined trust model creates a "trust synergy cycle," increasing productivity by nearly 100 percent. Finally, we show that a cobot operating in a Trust-Recovery Mode can overcome system brittleness after a disruption, reducing trust recovery time by over 75 percent compared to a non-adaptive model. Our findings provide a framework for designing intelligent cobot behaviors that fulfill the Industry 5.0 pillars of human-centricity, sustainability, and resilience. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_03765 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Synergy Over Spiral: A Logistics 5.0 Game-Theoretic Model for Trust-Fatigue Co-regulation in Human-Cobot Order Picking Dhar, Soumyadeep Saha, Ariyan Kumar Multiagent Systems This paper investigates the critical role of trust and fatigue in human-cobot collaborative order picking, framing the challenge within the scope of Logistics 5.0: the implementation of human-robot symbiosis in smart logistics. We propose a dynamic, leader-follower Stackelberg game to model this interaction, where utility functions explicitly account for human fatigue and trust. Through agent-based simulations, we demonstrate that while a naive model leads to a "trust death spiral," a refined trust model creates a "trust synergy cycle," increasing productivity by nearly 100 percent. Finally, we show that a cobot operating in a Trust-Recovery Mode can overcome system brittleness after a disruption, reducing trust recovery time by over 75 percent compared to a non-adaptive model. Our findings provide a framework for designing intelligent cobot behaviors that fulfill the Industry 5.0 pillars of human-centricity, sustainability, and resilience. |
| title | Synergy Over Spiral: A Logistics 5.0 Game-Theoretic Model for Trust-Fatigue Co-regulation in Human-Cobot Order Picking |
| topic | Multiagent Systems |
| url | https://arxiv.org/abs/2508.03765 |