Adaptive Door Opening Control Algorithm of Bio-Inspired Mobile Manipulator Based on Synchronous Sensing

Area of Science:

• Robotics
• Control Systems Engineering
• Artificial Intelligence

Background:

• Current robot door opening methods rely on pre-positioning and handle identification.
• Existing strategies lack robustness in handling uncertainties during operation.
• Synchronous sensing systems are crucial for coordinated robotic actions.

Purpose of the Study:

• To propose an adaptive door opening strategy for bio-inspired mobile manipulators.
• To enhance robot navigation and manipulation capabilities in complex environments.
• To address uncertainties in nonlinear systems for improved control.

Main Methods:

• Analysis of random delay distribution in clock synchronization technology.
• Target detection and tracking using depth network based on synchronous sensing data.
• Application of dynamic models for nonholonomic bio-inspired mobile manipulators.
• Development of a robust adaptive sliding mode control method combining adaptive backstepping and sliding mode control.

Main Results:

• Clock synchronization of network cable sensor nodes was achieved.
• Effective target detection and tracking were demonstrated.
• Simulations confirmed the effectiveness of the proposed robust adaptive sliding mode control method.
• The control strategy successfully compensated for system uncertainties and maintained trajectory stability.

Conclusions:

• The proposed adaptive door opening strategy is effective and feasible for bio-inspired mobile manipulators.
• The robust adaptive sliding mode control method enhances system stability and tracking performance.
• This research contributes to advancing autonomous robot navigation and interaction with the environment.