Robot Motion Control with Dynamic Task Priority Allocation

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Solution Overview

Problem

Existing robot control technologies struggle to dynamically adjust task priorities and reflect continuous changes in degrees of freedom required by tasks, leading to instability and reduced execution effectiveness when priority levels change.

Innovation Solution

A computer-implemented motion control method that calculates task and constraint matrices based on real-time state feedback and reference trajectory information, and constructs a hierarchical quadratic programming problem with recursive hierarchical projection to optimize task execution according to dynamic priority levels.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If the null space projection method or convex quadratic programming method is used to solve tasks in priority levels, then tasks can be solved in a unified mathematical form, but the complete projection relationship cannot directly reflect the continuous change of degrees of freedom when task priority levels are adjusted

Engineering Contradiction:

Improvetask priority adjustment capabilityVSAvoidoperation stability

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The patent applies dynamics by transforming the static complete projection relationship into a dynamic recursive hierarchical projection relationship. The projection matrix is updated recursively as task priorities change, allowing the system to adapt continuously rather than requiring complete recalculation. This dynamic update mechanism enables smooth transitions in degree of freedom allocation while maintaining operational stability.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The patent segments the unified task solving process into hierarchical levels with different priority weights. Instead of treating all tasks in a single unified mathematical form, the system divides tasks into multiple priority levels and solves them hierarchically, allowing independent adjustment of each level's contribution to the overall solution.

Inventive Principle:

Principle #1Segmentation

2Adaptability or versatility

If task priority levels are adjusted dynamically, then the robot can adapt to changing situations, but the execution effect and stability are affected due to inability to reflect continuous change in degrees of freedom

Engineering Contradiction:

Improvedynamic task priority adjustmentVSAvoidtask execution accuracy

Core Design Contradiction:

Adaptability or versatilityVSManufacturing precision

Solution Approach 1:

The patent changes parameters by introducing priority weight parameters that continuously adjust the contribution of different tasks. When task priorities change, the system modifies the weight parameters in the quadratic programming objective function, allowing smooth transitions in degree of freedom allocation without discrete jumps that would affect execution accuracy.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent implements feedback by continuously monitoring task execution status and priority levels, then adjusting the projection matrix and degree of freedom allocation accordingly. This closed-loop control ensures that changes in task priorities are reflected immediately in the motion planning, maintaining execution accuracy throughout the transition.

Inventive Principle:

Principle #23Feedback

3Ease of operation

If a complete projection relationship is used, then all tasks can be solved uniformly, but it cannot directly reflect continuous change when priority levels are adjusted, affecting robot operation stability

Engineering Contradiction:

Improveunified task solvingVSAvoidrobot operation stability

Core Design Contradiction:

Ease of operationVSStability of the object's composition

Solution Approach 1:

The patent transforms the static complete projection relationship into a dynamic recursive hierarchical projection relationship. The projection matrix is updated recursively as task priorities change, allowing the system to adapt continuously rather than requiring complete recalculation. This dynamic update mechanism enables smooth transitions in degree of freedom allocation while maintaining operational stability.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The patent prepares the projection matrix in advance for each priority level and stores them for quick retrieval and combination. This preliminary preparation allows the system to rapidly switch between different priority configurations without performing complete recalculation, maintaining both unified task solving capability and operational stability.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS12240119B2Motion control method, robot, and computer-readable storage medium

Publication Date: 2025.03.04 UBTECH ROBOTICS CORP LTD

AI summary

A motion control method, a robot, and a computer-readable storage medium are provided. The method includes: calculating a task matrix and expected information of each task of the robot based on reference trajectory information of each task of the robot in a control period and state estimation information of each task of the robot in the control period; calculating a constraint matrix and a boundary of an inequality constraint that the robot needs to satisfy based on the state estimation information; constructing a hierarchical quadratic programming problem with recursive hierarchical projection based on all the information obtained above, a real-time determined weight coefficient of each task, and a real-time determined priority level of each task: and solving the hierarchical quadratic programming problem to obtain a result, and generating a joint control instruction for controlling each joint of the robot to move.