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Color changing object recognition and grabbing technology based on crystal butterfly algorithm and adaptive

Zuoxun Wang1, Chuanyu Cui1, Jinxue Sui1

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Area of Science:

  • Robotics and Computer Vision
  • Artificial Intelligence

Background:

  • Grasping tasks in varied color and multi-scene conditions are crucial for robotic applications.
  • Existing methods for object recognition and grasping face limitations in speed and adaptability.

Purpose of the Study:

  • To develop an advanced recognition and grasping technique.
  • To enhance adaptability for multi-scene promotion of grasping technology.

Main Methods:

  • A 'Butterfly Trajectory' dynamic node tracking method inspired by butterfly movements.
  • Color Dynamic Recognition (CDR) technology for rapid multi-angle feature extraction (brightness, transparency, saturation).
  • Adaptive Imitation Synthesis (AIS) for multi-scenario grasping technology promotion, improving upon traditional HOG and R-CNN methods.

Main Results:

  • The Butterfly Trajectory method demonstrated effective dynamic trajectory tracking with route memory.
  • CDR technology significantly improved feature extraction speed compared to traditional methods.
  • AIS facilitated the successful multi-scenario promotion of grasping capabilities.

Conclusions:

  • The proposed crystal butterfly algorithm and adaptive imitation synthesis technique effectively address challenges in grasping tasks.
  • The study validates the proposed methods through simulation and physical testing, showing significant improvements in recognition and grasping capabilities.