Numerical Control for Redundant Axes Using Predictive Path Optimization
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Solution Overview
Problem
Existing control methods for processing machines with redundant axes require determining control signal groups for all path points in advance, which is time-consuming, especially for long sequences, and does not allow for real-time adjustment.
Innovation Solution
The numerical control determines control signal groups successively during activation of position-controlled axes, using a target function that minimizes position setpoints for the next path point, allowing for predictive control and reducing computational complexity by considering future path points, thereby enabling real-time movement without pre-determining all position setpoints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If control signal groups for all path points are determined in advance, then manufacturing precision is improved, but loss of time increases
Solution Approach 1:
The patent segments the path points into different categories: currently approached path points, future path points, and intermediate path points. The control signal determination is divided into phases where different sets of path points are considered at different times, allowing real-time control while maintaining precision for critical segments.
Solution Approach 2:
The patent performs preliminary determination of control signal groups for future path points before the robot actually reaches those points. By calculating position setpoints for future path points in advance (while the robot is still approaching current points), the system prepares control data ahead of time, reducing real-time computational burden without sacrificing precision.
2Manufacturing precision
If all position setpoints are determined in advance, then manufacturing precision is improved, but device complexity increases
Solution Approach 1:
The patent implements a dynamic control system where the set of path points considered for control signal determination changes over time. The system adapts which path points are included in the optimization based on the robot's current state, making the control approach flexible and reducing the need for complex pre-computation of all possible scenarios.
3Loss of time
If control is performed in real-time without pre-determination, then loss of time is reduced, but manufacturing precision deteriorates
Solution Approach 1:
The patent performs preliminary determination of control signal groups for future path points before the robot actually reaches those points. By calculating position setpoints for future path points in advance (while the robot is still approaching current points), the system prepares control data ahead of time, reducing real-time computational burden without sacrificing precision.
4Ease of operation
If redundant axes are explicitly programmed, then ease of operation is improved, but device complexity increases
Solution Approach 1:
The patent enables the numerical control system to automatically resolve the redundancy of multiple position-controlled axes by itself. The system independently determines the position setpoints for all axes based on the task requirements and kinematic constraints, without requiring the user to manually program each redundant axis. This makes the system easier to operate while managing the complexity internally.
Data Source
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AI summary
A program for a numerical control device is disclosed that determines path points to be approached by an end effector. A control signal group is ascertained for each path point that contains its set point value for each position-controlled axis. Those values are output to the axes, moving the end effector. The degrees of freedom are fewer than the position-controlled axes. The control signal groups are ascertained so that the end effector approaches the path points at least approximately. The control signal groups are ascertained gradually during the activation of the axes. The set point values are ascertained by minimizing an objective function. The objective function that is minimized includes at least the set point values for a path point only to be approached in the future. The sequence between the currently approached point and the point approached in the future has at least one further path point.