A framework of insole blanking robot based on adaptive edge detection and FSPS-BIT* path planning

Area of Science:

• Robotics and Automation
• Manufacturing Engineering
• Computer Vision

Background:

• Traditional insole blanking systems require precise workpiece positioning and auxiliary equipment, limiting flexibility.
• Existing robotic systems face challenges in adapting to varying lighting conditions during manufacturing processes.

Purpose of the Study:

• To develop an adaptive robotic system for insole blanking that overcomes limitations of current models.
• To enhance the precision and flexibility of insole production through intelligent automation.

Main Methods:

• An adaptive blanking robotic system integrating an industrial robot arm, RGB-D camera, and a custom blanking table.
• An edge detection framework using color features and morphological parameters optimized via particle swarm optimization (PSO).
• A path planning framework (FSPS-BIT*) combining FSPS and BIT* algorithms for efficient robotic arm movement.

Main Results:

• Successful adaptive recognition of insole edge contours under different lighting conditions.
• Efficient and precise path planning for the robotic arm in the blanking process.
• Demonstrated feasibility of the integrated robotic system for flexible insole production.

Conclusions:

• The proposed adaptive robotic system significantly improves insole blanking production by eliminating the need for precise pre-positioning.
• The innovative edge detection and path planning frameworks enable robust operation in variable lighting, enhancing manufacturing efficiency.
• This technology offers a flexible and precise solution for contemporary machining and manufacturing industries.