HUMAN-ROBOT COORDINATION IN INTELLIGENT WAREHOUSE SYSTEMS: AN ENGINEERING LOGISTICS MODEL FOR TASK ALLOCATION

Intelligent warehouses increasingly operate as mixed sociotechnical environments in which human operators, autonomous mobile robots (AMRs), information systems and material flows interact in real time. The central engineering question is therefore not whether robots should replace humans, but how tasks should be allocated so that operational performance improves without creating unacceptable physical, cognitive or safety burdens for workers. This conceptual study synthesizes recent research on human–robot collaboration in warehouses and proposes the HRT-A (Human-Robot Task Allocation) model. The model considers physical workload, cognitive complexity, safety relevance, spatial dynamics, urgency, the need for human judgement and expected logistics performance. It comprises five stages: task description, assessment of human workload, assessment of robotic suitability, selection of the executor and feedback. HRT-A is intended as a decision-support framework rather than as a validated optimization algorithm. Its contribution is to connect task allocation with human factors and warehouse performance while explicitly accounting for dynamic reassignment and responsibility when exceptions occur.