Manipulator Motion Control via Automatic Velocity Optimization
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Solution Overview
Problem
Existing methods for controlling industrial robots, such as specifying target paths and velocity profiles, often fail to fully utilize the robot's potential, particularly when constant velocity is manually chosen, leading to suboptimal performance in tasks like uniform adhesive application.
Innovation Solution
A method to determine and implement motion values, including velocity, acceleration, and jerk profiles along a target path, automatically ensuring compliance with drive limitations and optimizing motion to achieve maximum permissible speeds and torques, using spline functions and dynamic models to define path segments with constant or varying motion values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If constant velocity is manually chosen for the target path, then the velocity profile can be simply defined, but the robot's potential is not fully utilized and productivity is reduced
Solution Approach 1:
The control device automatically determines the motion values by evaluating the dynamic model and drive limitations itself, without requiring manual optimization. The system serves itself by computing the optimal constant velocity that maximizes productivity while respecting all constraints, eliminating the need for operator intervention in velocity selection.
Solution Approach 2:
The system dynamically adjusts the velocity parameter based on the evaluated drive limitations and dynamic model. Instead of using a fixed manually-chosen velocity, the control device computes the optimal velocity value that changes according to the robot's current state and constraints, thereby maximizing productivity.
2Productivity
If maximum velocity is used to maximize productivity, then productivity improves, but drive limitations and safety constraints may be violated
Solution Approach 1:
The control device performs preliminary evaluation of the dynamic model and drive limitations before executing the motion. By pre-calculating the maximum permissible constant velocity that satisfies all constraints, the system ensures that productivity is maximized without violating safety or mechanical limits during actual operation.
Solution Approach 2:
The system uses feedback from the dynamic model evaluation to adjust the velocity command. The control device continuously monitors drive limitations and adjusts the motion values accordingly, ensuring that the robot operates at the maximum safe velocity that respects all constraints while maintaining reliability.
3Productivity
If velocity profile is automatically optimized, then productivity increases, but control complexity increases
Solution Approach 1:
The control device segments the target path into path segments and evaluates each segment independently. By dividing the motion planning into manageable segments, the system can apply automatic optimization without overwhelming complexity, processing each segment's constraints and dynamics separately to determine optimal motion values.
Solution Approach 2:
The control device acts as an intermediary between the simple constant velocity requirement and the complex dynamic constraints. It translates the user's simple velocity specification into optimized motion commands by evaluating the dynamic model and drive limitations, thereby bridging the gap between simplicity and optimality without requiring the user to understand complex dynamics.
Data Source
AI summary
A method according to the invention for controlling a manipulator, in particular a robot, includes the following steps:determining (S10, S20) a target path (q(s)) of the manipulator, anddetermining (S70) a motion value (v(s)) for this target path,optionally, determining (S50) a path segment ([s_A, s_E]) with a defined profile of a motion value (v(s)=vc), and automatically determining (S60) this motion value on the basis of motion values (v_max_RB, v_max_vg) permissible in this path segment.