Trajectory Consensus for Coordination of Multiple Curvature-Bounded Vehicles

Area of Science:

• Robotics
• Control Systems
• Autonomous Vehicles

Background:

• Coordinating multiple vehicles requires trajectory consensus.
• Existing methods often treat vehicle states in isolation.
• Achieving geometric consensus of planned trajectories is crucial for safe and efficient multi-vehicle systems.

Purpose of the Study:

• To address the trajectory consensus problem for multiple vehicles.
• To achieve consensus on the geometry of planned vehicle trajectories.
• To develop an improved method for coordinating multi-vehicle movements.

Main Methods:

• Parameterizing trajectory geometry using trajectory states (required lengths to reach specific distances from the endpoint).
• Extending the conventional consensus model with a mapping from state variables to trajectory geometry.
• Utilizing a homotopic structure for compact and efficient mapping.
• Employing a homotopic search to achieve asymptotic consensus.

Main Results:

• The proposed coupled state consensus method demonstrates superior performance in achieving trajectory geometry consensus for multiple vehicles.
• Simulation results validate the effectiveness of the new approach over conventional isolated state consensus methods.
• The homotopic structure provides an efficient way to link state variables to trajectory geometry.

Conclusions:

• The coupled state consensus method offers a significant advancement in multi-vehicle trajectory coordination.
• This approach enhances the geometric consensus of planned trajectories, leading to improved system performance.
• The use of homotopic structures provides a novel and effective framework for solving complex consensus problems in robotics and control systems.