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Operation of the Collaborative Composite Manufacturing CCM System

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A Human-Following Motion Planning and Control Scheme for Collaborative Robots Based on Human Motion Prediction.

Fahad Iqbal Khawaja^1,2, Akira Kanazawa¹, Jun Kinugawa¹

¹Center for Transformative AI and Robotics, Graduate School of Engineering, Tohoku University, Sendai 980-8579, Japan.

Sensors (Basel, Switzerland)

|December 28, 2021

Summary

This study introduces a new human-following system for collaborative robots, ensuring workers feel safe and comfortable. The system uses predictive control to deliver parts and tools efficiently during factory assembly tasks.

Keywords:

collaborative robots human motion prediction human-following robots human–robot collaboration human–robot interaction motion planning robot control

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Area of Science:

Robotics
Human-Robot Interaction
Automation

Background:

Collaborative robots enhance worker efficiency in assembly lines.
Ensuring worker safety and comfort during human-robot interaction is crucial.
Existing systems often lack dynamic adaptation to worker movement.

Purpose of the Study:

To develop a human-following motion planning and control scheme for collaborative robots.
To enable robots to dynamically supply parts and tools to moving workers.
To ensure worker safety and comfort in an industrial assembly setting.

Main Methods:

Utilized a 3-D sensing system to capture real-time worker skeletal data.
Employed probabilistic prediction of future worker positions.
Implemented a Model Predictive Control (MPC)-based trajectory planner for robot motion.
Integrated the scheme into a 2-DOF planar manipulator collaborative robot system.

Main Results:

The proposed scheme successfully enabled the collaborative robot to follow a moving worker.
The robot effectively supplied necessary parts and tools to the worker.
Experimental results demonstrated enhanced safety and comfort for the worker.
The system provided continuous assistance to workers moving within the workspace.

Conclusions:

The developed human-following system enhances collaborative robot functionality in dynamic assembly tasks.
The integration of real-time sensing, predictive control, and MPC ensures safe and comfortable human-robot collaboration.
This approach offers a significant advancement in adaptive robotic assistance for industrial environments.