Flexible sensor concept and an efficient integrated sensing controlling for an efficient human-robot collaboration...

Area of Science:

• Robotics
• Manufacturing Engineering
• Sensor Technology

Background:

• Human-robot collaboration is crucial for agile manufacturing but limited by current collision avoidance systems.
• Existing systems reduce operational efficiency due to the need for constant human presence and robot speed limitations.

Purpose of the Study:

• To develop a novel local and global sensing framework for enhanced human-robot collaboration.
• To improve operational efficiency and safety in agile manufacturing processes.

Main Methods:

• Proposed a flexible sensor concept using 2D or 3D LiDAR, addressing robot body occlusion.
• Extended sensing methodology with co-moving 3D sensors on the robot body.
• Developed an efficient method for estimating sensing and control sub-system sensitivity and reactivity.

Main Results:

• Integrated local-global sensing methods allow for high robot speeds, increasing process efficiency.
• The framework ensures human safety during collaborative tasks.
• Demonstrated sensor flexibility with a heavy-duty industrial robot, 3D LiDAR, and camera.

Conclusions:

• The proposed sensing framework significantly improves efficiency and safety in human-robot collaboration.
• This approach enables faster industrial robot operations in agile manufacturing settings.
• The methodology offers a flexible and robust solution for collaborative robotics.