Robot Motion Trajectory Planning for Complex High-Precision Moves
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Solution Overview
Problem
Current robot technologies struggle to perform complex and time-consuming movements with high quality, as they are limited in accurately completing intricate motions due to limitations in motion control and trajectory generation.
Innovation Solution
A motion control method that generates motion phases and determines desired poses for robots based on the type of motion, using a cost function model to optimize trajectories, including control parameters at each sampling point, allowing for precise control and completion of complex movements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional motion control methods are used, then simple repetitive movements can be realized with high quality, but complex and time-consuming movements cannot be completed with high quality
Solution Approach 1:
The motion process is divided into multiple motion phases, with each phase having specific start and end poses. This segmentation allows the complex motion to be broken down into manageable segments that can be optimized and controlled independently, enabling both high complexity and high precision to be achieved simultaneously
Solution Approach 2:
The desired poses at key nodes are determined in advance based on the motion type and phase division. By pre-defining these critical poses before execution, the system prepares the optimal trajectory points ahead of time, allowing complex motions to be executed with high precision without real-time computational delays
2Adaptability or versatility
If more complex movements are attempted, then motion versatility is improved, but the ability to complete movements with high quality deteriorates
Solution Approach 1:
The cost function model dynamically adjusts the trajectory optimization based on the specific motion type and phase characteristics. By making the optimization criteria adaptive rather than fixed, the system can handle diverse motion types while maintaining high completion accuracy through real-time parameter adjustment
Solution Approach 2:
The cost function model evaluates and optimizes the trajectory by comparing desired poses with actual motion states. This feedback mechanism ensures that even complex movements are corrected and refined during execution, maintaining high reliability and completion accuracy across various motion types
Data Source
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AI summary
The present disclosure provides a motion control method and apparatus, and a method and apparatus for generating a trajectory of a motion. The motion control method is applied to a robot, and includes: generating, according to a type of a desired motion, at least one motion phase of a motion process and a time for each motion phase; determining, according to the at least one motion phase and the time of each motion phase, a desired pose of the robot at at least one node during the motion process; inputting the desired pose as a reference value into a cost function model to obtain a trajectory of the desired motion, where the trajectory includes a pose and a control parameter of the robot at each sampling point during the motion process; and controlling the robot to move according to the trajectory of the desired motion.