Null-space-based modulated reference trajectory generator for multi-robots formation in obstacle environment.

Area of Science:

• Robotics
• Control Systems
• Artificial Intelligence

Background:

• Multi-robot systems require sophisticated control for coordinated movement.
• Obstacle avoidance is a critical challenge in real-world robotic applications.
• Maintaining formation stability during navigation is essential for mission success.

Purpose of the Study:

• To address the 3D formation problem for multi-robots operating in environments with obstacles.
• To develop a control strategy that ensures formation error convergence to zero.
• To achieve obstacle and collision avoidance while respecting system constraints.

Main Methods:

• Utilizing nonlinear model predictive control (NMPC) as the core solution framework.
• Proposing a null-space-based modulated reference trajectory generator.
• Modulating robot velocities based on obstacle presence and integrating them using null space.

Main Results:

• Demonstrated effective obstacle and collision avoidance.
• Proved that formation system stability is maintained.
• Simulation results confirmed the method's high efficiency and robustness.

Conclusions:

• The proposed method successfully enables multi-robots to achieve desired formations in 3D obstacle environments.
• The null-space-based modulation ensures safe navigation without compromising formation integrity.
• The NMPC framework provides a stable and robust solution for complex robotic tasks.