Robot Control Using Relative Object Relations for Versatile Operation

Solution Overview

Problem

Conventional robot control methods lack versatility, requiring new learning when environmental or object changes occur, leading to high teaching costs due to direct association of time-series control commands with specific operations.

Innovation Solution

A control device that generates control commands based on relative relationship amounts between objects, allowing the robot to adapt to changes by determining a series of relative relationship amounts from a starting state to a final target state, enabling the execution of operations with the same change in relative relationship amounts regardless of the operation details.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If time-series control commands are directly associated with specific operations through manual teaching or conventional learning, then the robot can execute the taught operation accurately, but the teaching cost increases significantly when components or environment changes occur

Engineering Contradiction:

Improveoperation execution accuracyVSAvoidversatility of operation execution

Core Design Contradiction:

ReliabilityVSAdaptability or versatility

Solution Approach 1:

The patent transforms the control approach by changing the parameter representation from absolute time-series commands to relative relationship amounts between objects. This parameter transformation allows the same control logic to adapt to different object configurations and environmental conditions without requiring re-teaching, thereby resolving the contradiction between execution accuracy and adaptability

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent transforms the control approach by changing the parameter representation from absolute time-series commands to relative relationship amounts between objects. This parameter transformation allows the same control logic to adapt to different object configurations and environmental conditions without requiring re-teaching, thereby resolving the contradiction between execution accuracy and adaptability

Inventive Principle:

Principle #35Parameter changes

2Reliability

If the robot is taught operations for each specific component configuration through manual teaching, then the operation can be performed accurately for that configuration, but the teaching cost becomes too high to be practical

Engineering Contradiction:

Improveoperation execution accuracyVSAvoidteaching cost

Core Design Contradiction:

ReliabilityVSEase of manufacture

Solution Approach 1:

The patent creates a universal control method that can handle multiple component configurations and operational scenarios with a single learning process. By focusing on relative relationships rather than absolute positions, the system achieves multi-functionality across different mechanical configurations, end effectors, and environmental conditions, dramatically reducing teaching costs while maintaining accuracy

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent transforms the control approach by changing the parameter representation from absolute time-series commands to relative relationship amounts between objects. This parameter transformation allows the same control logic to adapt to different object configurations and environmental conditions without requiring re-teaching, thereby resolving the contradiction between execution accuracy and adaptability

Inventive Principle:

Principle #35Parameter changes

3Reliability

If the robot learns operations based on fixed environmental conditions and object positions, then the learned operation can be executed accurately under those specific conditions, but the robot cannot adapt when the environment or object placement varies

Engineering Contradiction:

Improveoperation execution accuracyVSAvoidadaptability to environmental changes

Core Design Contradiction:

ReliabilityVSAdaptability or versatility

Solution Approach 1:

The patent introduces dynamic adaptability by making the control system respond to real-time relative relationships between objects rather than following fixed absolute trajectories. The system continuously updates control commands based on current object positions and configurations, enabling it to adapt to environmental changes while maintaining execution accuracy through the learned relative relationship patterns

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS11745355B2Control device, control method, and non-transitory computer-readable storage medium

Publication Date: 2023.09.05 OMRON CORP

AI summary

A control device sets a relative relation amount between a plurality of target objects that are to be final objectives, repeatedly acquires observation data from a sensor and calculates the relative relation amount between the plurality of target objects existing in the environment from the acquired observation data. Further, the control device determines a series of the relative relation amounts in a state that is to be an objective from the relative relation amount at a time point at which control of the behavior starts until the relative relation amount as the final objectives is realized, and repeatedly determines control instructions so as to change the relative relation amount in a present state calculated from the latest observation data into the relative relation amount in a state of an objective to be transitioned to next. Then, the control device outputs the determined control instruction to a robot device.