Ergonomics Analysis for a Simulation Approach to Human-Robot Collaborative Task Allocation

Area of Science:

• Human-robot interaction
• Occupational ergonomics
• Robotics

Background:

• Traditional task allocation can lead to operator strain and inefficiency.
• Integrating collaborative robots requires optimized methods for task distribution.
• Ergonomics interventions are crucial for worker well-being and productivity.

Purpose of the Study:

• To develop and evaluate an algorithmic approach for task assignment between human workers and collaborative robots.
• To optimize task allocation based on ergonomics cost, considering force and time.
• To assess the impact of this optimized allocation on operator stress and job cycle time.

Main Methods:

• An algorithmic approach was employed to dynamically assign tasks.
• Optimization criteria included force exertion and time duration as measures of ergonomics cost.
• Tasks were categorized based on physical demand (e.g., applying forces) and dexterity requirements (e.g., part alignment).

Main Results:

• The algorithm assigned physically demanding tasks, such as force application, to the robot.
• Dexterous tasks, like part alignment, were assigned to the human worker.
• Operator stress levels were reduced, and the overall job cycle time decreased.

Conclusions:

• Algorithmic task allocation can effectively balance workload between humans and collaborative robots.
• This method enhances ergonomics by assigning tasks based on physical demands and dexterity.
• The approach shows promise for improved integration of collaborative robots in occupational settings.