Autonomous Robot Interface for Real-Time Picking Error Correction

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Solution Overview

Problem

Autonomous computing systems face challenges in detecting and correcting errors during tasks, such as incorrect object retrieval or deposition, in real-time, due to the lack of effective error detection and communication mechanisms.

Innovation Solution

An automatic interfacing system is implemented, comprising autonomous robot devices equipped with sensors and computing systems that detect errors through attribute detection and establish communication interfaces to correct tasks, allowing operators to communicate and re-route robots as needed.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If autonomous robot devices perform tasks independently without external monitoring, then productivity and automation extent are improved, but error detection capability deteriorates

Engineering Contradiction:
Improvetask execution efficiencyVSAvoiderror detection capability
Core Design Contradiction:
ProductivityVSReliability

Solution Approach 1:

The system implements a feedback mechanism where sensors continuously monitor robot operations and transmit data to computing systems. The computing systems analyze sensor outputs to detect errors in real-time, creating a closed-loop control system that maintains both high automation and reliable error detection through continuous information feedback about system state

Inventive Principle:
Principle #23Feedback

Solution Approach 2:

Sensors act as intermediary components between the autonomous robot devices and the computing systems. These sensors detect operational parameters and transmit information to the computing systems, enabling indirect monitoring and error detection without requiring direct human observation or intervention in the autonomous operations

Inventive Principle:
Principle #24Intermediary (Mediator)

2Measurement precision

If multiple sensors are deployed to detect errors in real-time, then error detection precision is improved, but device complexity increases

Engineering Contradiction:
Improveerror detection precisionVSAvoidsystem complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The computing systems perform multiple functions: they receive data from various sensors, process this information to detect errors, communicate with robot devices, and coordinate operations. By making the computing systems multi-functional, the patent reduces the need for separate dedicated components for each function, thereby managing complexity while maintaining high error detection precision through integrated processing

Inventive Principle:
Principle #6Universality (Multi-functionality)

3Device complexity

If autonomous robots operate without communication interfaces, then device complexity is reduced, but ease of operation deteriorates when errors occur

Engineering Contradiction:
Improvecommunication interface complexityVSAvoiderror correction capability
Core Design Contradiction:
Device complexityVSEase of operation

Solution Approach 1:

Communication interfaces serve as intermediaries that enable operators to interact with autonomous robot devices when errors are detected. These interfaces provide a structured way for operators to receive error information from sensors and computing systems, and to send corrective commands back to the robots, making error correction accessible without requiring deep technical knowledge of the autonomous systems

Inventive Principle:
Principle #24Intermediary (Mediator)

Data Source

PatentUS11707839B2Distributed autonomous robot interfacing systems and methods
Publication Date: 2023.07.25 WALMART APOLLO LLC
  • US11707839B2 patent drawing
  • US11707839B2 patent drawing
  • US11707839B2 patent drawing

AI summary

Described in detail herein is an automated fulfilment system including a computing system programmed to receive requests from disparate sources for physical objects disposed at one or more locations in a facility. The computing system can combine the requests, and group the physical objects in the requests based on object types or expected object locations. Autonomous robot devices can receive instructions from the computing system to retrieve a group of the physical objects and deposit the physical objects in storage containers.