Fixed-time formation behavior control for unmanned ground vehicle-manipulators.

Area of Science:

• Robotics and Autonomous Systems
• Control Theory
• Artificial Intelligence

Background:

• Unmanned Ground Vehicle-Manipulators (UGVMs) integrate mobility and manipulation, facing challenges in formation control due to nonholonomic constraints, disturbances, and multi-task conflicts.
• Existing methods struggle with rapid convergence and robust handling of uncertainties in complex operational environments.

Purpose of the Study:

• To propose a fixed-time formation behavior control (Fixed-FBC) method for UGVMs operating in static obstacle environments.
• To address challenges including nonholonomic constraints, external disturbances, and system uncertainties for improved formation control.

Main Methods:

• Developed a nonholonomic null-space behavioral control (N-NSBC) framework integrating fixed-time stability for rapid convergence.
• Incorporated nonholonomic constraints to avoid local minima by resolving yaw-position coupling and unified multi-objective coordination into velocity commands.
• Designed an adaptive fixed-time tracking controller using adaptive laws for parameter estimation and sliding mode techniques for disturbance rejection.

Main Results:

• Achieved a significant reduction in settling time compared to conventional methods.
• Demonstrated effective coordination of formation maintenance, static obstacle avoidance, and manipulator control.
• Validated the robustness of the proposed method against system uncertainties and external disturbances.

Conclusions:

• The Fixed-FBC method offers a robust and efficient solution for UGVM formation control in complex environments.
• The N-NSBC framework effectively handles nonholonomic constraints and multi-objective coordination.
• The adaptive fixed-time controller ensures rapid convergence and resilience to uncertainties and disturbances.