Robot Manipulator Control for Shared Workspace Safety Constraints
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Solution Overview
Problem
Conventional control methods for robot manipulators in shared workspaces with humans face issues of human safety, task consistency, and compatibility with different control modes, such as joint-position, joint-velocity, joint-acceleration, and joint-torque control modes, leading to potential collisions and unresumable task failures.
Innovation Solution
A method and system that determine safety, hard, and soft constraint control sets using a safety control function, hard constraint function, and soft constraint function, respectively, to optimize control inputs for the robot manipulator, ensuring human safety and task consistency across various control modes by employing a control affine form and sliding manifold-based control barrier functions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional APF-inspired methods are used for collision avoidance, then the robot can generate evasive motion to avoid collision with humans, but human safety is not always guaranteed because the parameters are set empirically
Solution Approach 1:
The patent transforms the empirical parameter setting approach into a systematic parameter optimization process. By formulating the safety guarantee as a constraint satisfaction problem with optimized parameters, the system transitions from fixed empirical values to dynamically optimized parameters that adapt to different operational contexts, thereby improving reliability while maintaining manageable complexity.
Solution Approach 2:
The patent implements feedback mechanisms by continuously monitoring human-robot distance and adjusting control parameters in real-time. The control system uses feedback from distance measurements to dynamically modify evasive motion parameters, ensuring that safety constraints are continuously satisfied rather than relying on pre-set empirical values.
2Reliability
If conventional control methods are configured for specific control modes, then control performance for that mode is optimized, but adaptability to other control modes is lost
Solution Approach 1:
The patent implements universality by formulating a unified constraint satisfaction framework that can accommodate multiple control modes (joint-position, joint-velocity, joint-acceleration, joint-torque). The same mathematical framework and optimization approach work across all control modes, allowing the system to adapt to different modes without requiring mode-specific implementations.
Solution Approach 2:
The patent segments the control problem into independent constraint satisfaction components that can be applied uniformly across different control modes. By dividing the overall control task into separate constraint handling modules (safety constraints, task constraints, performance constraints), the system can adapt to different control modes by applying the same segmented framework to each mode's specific parameters.
Data Source
AI summary
A method of controlling a robot manipulator for operating in a shared workspace with human(s) is provided. The method includes: determining a safety control set with respect to a safety condition between selected part(s) of the robot manipulator and selected part(s) of the human(s) using a safety control function: determining a hard constraint control set with respect to hard constraint(s) in trajectory tracking in DOF(s) of a component of the robot manipulator for a task using a hard constraint function: determining a soft constraint control set with respect to soft constraint(s) in trajectory tracking in DOF(s) of the component for the task using a soft constraint function: and performing control input optimization based on the safety control set. the hard constraint control set and the soft constraint control set to determine a control input for controlling the robot manipulator. In particular, the safety control function is configured to determine the safety control set: based on a control model for the robot manipulator that is configured in a control affine form based on a control mode of the robot manipulator, and for each part pair of part pair(s) of a selected part of the selected part(s) of the robot manipulator and a selected part of the selected part(s) of the human(s): based on a safety distance function associated with the part pair which corresponds to a control barrier function, and based on a sliding manifold associated with the part pair configured based on the safety distance function and a relative degree of the safety distance function with respect to the control input to the robot manipulator.