Unactuated and Actuated States Simultaneously Constrained Optimal Trajectory Planning-Based Path-Following Control...

Area of Science:

• Robotics
• Control Systems
• Optimization

Background:

• Underactuated robots in complex environments require advanced control beyond point-to-point methods.
• Existing path planning methods often fail for underactuated systems or rely on simplified models.
• Controlling unactuated states, like crane payload swing, presents significant challenges.

Purpose of the Study:

• To develop a novel motion control method for general underactuated robots.
• To achieve path following and satisfy motion constraints for both actuated and unactuated states.
• To enable time-optimal trajectory planning for underactuated systems lacking direct control inputs.

Main Methods:

• A new time-optimal trajectory planning-based motion control method is proposed.
• Auxiliary signals in Cartesian space are used to represent joint-space variables.
• Position/velocity constraints are transformed into optimization inequalities for a path parameter.

Main Results:

• The method successfully converts full-state constraints into solvable optimization problems.
• Time-optimal trajectories are derived for actuated states, ensuring path following.
• The approach achieves a balance between path constraints, time optimization, and state limitations.

Conclusions:

• This work presents the first method to ensure path following and full-state constraints for underactuated systems.
• The proposed framework is validated through analysis and hardware experiments on a rotary crane.
• The method offers a robust solution for controlling underactuated robots in complex scenarios.