Trajectory Planning for Coal Gangue Sorting Robot Tracking Fast-Mass Target under Multiple Constraints

Area of Science:

• Robotics
• Control Engineering
• Artificial Intelligence

Background:

• Robot manipulator failures and damage often result from impact loads during target grasping.
• Impact loads occur due to speed differences between the manipulator end-effector and the dynamic target.
• Existing methods struggle with multi-constraint trajectory planning for synchronous tracking.

Purpose of the Study:

• To propose a dynamic gangue trajectory planning method for manipulator synchronous tracking under multi-constraint conditions.
• To address issues of grab failure and manipulator damage in robotic grasping operations.
• To enhance the stability and success rate of robotic grasping through accurate target tracking.

Main Methods:

• Constructed a mathematical model for seven-segment manipulator trajectory planning.
• Developed a model for synchronous tracking of dynamic targets, optimizing for minimum time under acceleration, speed, and synchronization constraints.
• Utilized the particle swarm optimization algorithm to solve the multi-constraint problem, transforming it into a single-objective problem.

Main Results:

• The proposed method generates a synchronous tracking trajectory for the manipulator.
• Simulations and experiments confirmed that robot arm joints can synchronously track dynamic targets within specified constraints.
• Achieved high tracking accuracy with an average position error of 2.1 mm and average speed error of 7.4 mm/s.

Conclusions:

• The developed method effectively ensures synchronization of position, speed, and acceleration between the manipulator and dynamic targets.
• This approach significantly improves robot grasping stability and success rates.
• The trajectory planning method offers a robust solution for dynamic target tracking in robotic applications.