Robot Arm Trajectory Planning for Collision-Safe Substrate Transfer
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Solution Overview
Problem
Conventional robot arm trajectory control systems in manufacturing environments are inefficient, leading to increased time, energy consumption, processing overhead, and bandwidth usage, which can result in substrate damage and equipment damage due to collision risks and low yield.
Innovation Solution
A method that identifies a sequence of robot configurations and generates motion planning data including velocity and acceleration data to optimize the trajectory of a robot arm, avoiding collisions by using nonlinear optimization and shortest path planning, thereby minimizing distance and time while actuating the robot arm based on this data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional robot arm trajectory control systems are used, then the robot arm can transfer substrates, but the system experiences increased time consumption, energy consumption, and processing overhead
Solution Approach 1:
The system pre-calculates the entire trajectory including all configuration sequences, velocity profiles, and acceleration data before the robot arm begins movement. This preliminary computation of the complete motion plan eliminates real-time calculation delays during execution, directly reducing trajectory execution time while maintaining efficient substrate transfer
Solution Approach 2:
The trajectory control system dynamically optimizes velocity and acceleration parameters for each portion of the trajectory based on pre-calculated motion planning data. This dynamic adjustment of motion parameters allows the robot arm to execute movements more efficiently, reducing overall execution time while ensuring safe and accurate substrate transfer
2Reliability
If conventional trajectory control is used, then substrate transfer is performed, but collision risks increase leading to substrate damage and equipment damage
Solution Approach 1:
The system performs preliminary collision risk assessment and trajectory validation before the robot arm executes movement. By pre-calculating safe trajectories and verifying collision-free paths in advance, the system eliminates collision risks during actual substrate transfer, protecting both substrates and equipment from damage
Solution Approach 2:
The trajectory control system incorporates feedback mechanisms that monitor robot arm position and trajectory adherence in real-time during execution. This feedback ensures the robot arm follows the pre-calculated safe trajectory precisely, detecting and correcting any deviations that could lead to collisions, thereby maintaining high reliability and preventing substrate or equipment damage
3Productivity
If conventional motion control systems are used, then robot arm movement is controlled, but energy consumption and processing overhead increase
Solution Approach 1:
The system pre-calculates energy-optimized velocity and acceleration profiles for each trajectory portion before execution. By determining the most energy-efficient motion parameters in advance based on the pre-computed trajectory, the robot arm minimizes energy consumption during substrate transfer while maintaining high processing efficiency
Solution Approach 2:
The trajectory control system dynamically adjusts velocity and acceleration parameters during robot arm movement based on pre-calculated optimization data. By changing these motion parameters according to the optimized profile, the system reduces energy consumption while maintaining productive substrate transfer rates
4Manufacturing precision
If complex trajectory calculations are performed in real-time, then accurate robot arm control is achieved, but processing overhead and bandwidth usage increase
Solution Approach 1:
The system performs all complex trajectory calculations, configuration sequencing, and motion planning in advance before robot arm execution. By completing these computationally intensive tasks preliminarily and storing the results as execution instructions, the system achieves high trajectory accuracy during movement without incurring real-time processing overhead or bandwidth consumption
Data Source
AI summary
A method includes identifying a sequence of robot configurations associated with processing a plurality of substrates. The method further includes generating motion planning data comprising corresponding velocity data and corresponding acceleration data for each portion of a trajectory associated with the processing of the plurality of substrates. The method further includes causing a robot arm to be actuated based on the motion planning data.


