Hosseini, Ziagul; Le Blanc, Pascale; Demerouti, Evangelia; van Gool, Piet; van den Tooren, Marieke; Preenen, Paul T Y

Implementing collaborative robots in warehouse operations requires employees to engage in order picking alongside robots, which raises concerns about employees' perception of being 'robotised'. This study explores the interplay between workload and autonomy in the context of Automated Guided Vehicle (AGV)-assisted order picking, aiming to understand their joint impact on employees' boredom and performance. In a unique controlled laboratory experiment conducted within an experimental warehouse environment, order pickers interacted with an actual AGV to retrieve items from various aisles and deliver them to a depot station. Participants in the high-workload low-autonomy condition were less bored but performed poorer than those in the low-workload low-autonomy condition. No significant differences in boredom and performance between the low-workload high-autonomy condition and the high-workload high-autonomy condition were found. Our findings emphasise the importance of considering the effects on employees when implementing AGV-assisted order picking. To reduce order pickers' boredom caused by such tasks, autonomy should be provided while ensuring that they do not have a workload that is too high, which could harm performance.

At the conclusion of this event, attendees will be able to:
- Recognise the significance of autonomy for employees who are collaborating with advanced technologies in the order picking process. Specific examples include giving employees control over their tasks by involving them in task planning and execution, and offering decision-making opportunities, such as choosing when to move to the next picking location, which can further enhance their autonomy.
- Understand the importance of managing workload to prevent boredom and performance issues in AGV-assisted picking. Strategies like workload balancing and task rotation can help them maintain optimal workload levels.
- Effective training on using advanced robotics in the workplace and continuous evaluation and refinement based on employee feedback and performance metrics are vital for maximising benefits while minimising drawbacks on employees' motivation and their performance.