Adaptive Skid-Steering Control Approach for Robots on Uncertain Inclined Planes with Redundant Load-Bearing Mobility.

Area of Science:

• Robotics
• Control Systems Engineering
• Manufacturing Technology

Background:

• Climbing manufacturing robots (CMo-Rs) offer revolutionary potential for large component fabrication.
• Motion control for CMo-Rs faces significant challenges, particularly concerning anti-slippage on diverse surfaces.
• Existing control methods may not adequately address the complexities of uncertain inclined planes.

Purpose of the Study:

• To design and validate an adaptive kinematic control algorithm for CMo-Rs that accounts for slip phenomena.
• To enhance the trajectory tracking accuracy and stability of CMo-Rs across various terrains, including inclined and vertical planes.
• To demonstrate the superiority of the proposed slip-estimating control over traditional PID control.

Main Methods:

• Design of a magnetic adsorption-based CMo-R with redundant mobility.
• Development of a four-wheel kinematic model incorporating slip dynamics.
• Implementation of an adaptive kinematic control algorithm using Lyapunov theory for slip estimation.
• Comparative numerical simulations and experimental validation against a traditional PID controller.

Main Results:

• The proposed adaptive control algorithm significantly improved trajectory tracking accuracy on horizontal, inclined (50°, 60°), and vertical planes.
• The algorithm demonstrated robust performance even on uncertain inclined planes, outperforming the traditional PID controller.
• Experimental results validated the feasibility, applicability, and stability of the developed control approach.

Conclusions:

• The adaptive kinematic control algorithm effectively addresses anti-slippage challenges in CMo-Rs.
• The developed approach enhances robotic manufacturing precision and applicability for large, complex components in diverse environments.
• This research advances the motion control of climbing robots for industrial manufacturing.