Geometric Parameter Identification of Medical Robot Based on Improved Beetle Antennae Search Algorithm.

Area of Science:

• Robotics
• Medical Engineering
• Artificial Intelligence

Background:

• Accurate identification of geometric errors is crucial for medical robot precision.
• Existing intelligent algorithms face challenges in identifying these parameters effectively.

Purpose of the Study:

• To propose an improved beetle antennae search algorithm (RWSAVSBAS) for enhanced geometric error parameter identification in medical robots.
• To increase the accuracy of medical robot end-positioning.

Main Methods:

• Developed a kinematic error model for medical robots.
• Integrated wolf colony algorithm's random wandering for improved local search.
• Applied simulated annealing to enhance global convergence of the beetle antennae search algorithm.

Main Results:

• The RWSAVSBAS algorithm demonstrated superior convergence accuracy compared to existing methods.
• Simulations confirmed a significant improvement in the accuracy of medical robot end-positioning.

Conclusions:

• The RWSAVSBAS algorithm offers a more accurate approach to identifying geometric errors in medical robots.
• This advancement contributes to enhanced precision and reliability in medical robotic applications.