Autonomous Robot Inventory Tracking via Dual-Surface Barcode Scanning
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Solution Overview
Problem
Tracking and updating the quantity of physical objects in large facilities is difficult and inefficient, as existing methods lack automation and accuracy.
Innovation Solution
An autonomous robot system equipped with optical scanners and inertial navigation, capable of detecting machine-readable representations on shelving units, determines the presence or absence of physical objects by reading identifiers on both the front and back surfaces, and communicates with a computing system to trigger alerts or replenishment when objects are missing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual tracking methods are used to monitor physical objects in large facilities, then the system complexity is low, but the productivity and accuracy of inventory tracking deteriorate
Solution Approach 1:
The patent replaces manual mechanical tracking with an autonomous robot system equipped with optical scanners and inertial navigation. The robot autonomously navigates through facilities, scans machine-readable representations on shelving units, and automatically updates inventory databases, eliminating the need for manual counting while significantly improving tracking speed and accuracy.
Solution Approach 2:
The autonomous robot performs self-navigation and self-monitoring tasks without human intervention. It uses its onboard sensors and navigation systems to autonomously move through the facility, detect inventory items, and communicate findings to the central system, enabling the system to service itself rather than requiring manual operation.
2Loss of time
If manual inventory updating is performed, then the device complexity is low, but the time required to update inventory quantities increases
Solution Approach 1:
The autonomous robot enables continuous inventory monitoring by continuously navigating through the facility and scanning shelving units. Rather than periodic manual updates, the system maintains continuous awareness of inventory status, dramatically reducing the time loss associated with inventory updates while the robot operates autonomously throughout the facility.
3Measurement precision
If automated robot systems are deployed for object detection, then the productivity and accuracy of tracking improve, but the device complexity increases
Solution Approach 1:
The autonomous robot system divides the inventory tracking task into separate functional modules: navigation (inertial navigation system), detection (optical scanners), identification (machine-readable representation recognition), and communication (data transmission to central system). This segmentation allows each component to be optimized independently while working together to achieve high detection accuracy.
Solution Approach 2:
The patent uses machine-readable representations (barcodes, QR codes, or other optical identifiers) as intermediaries between the physical objects and the detection system. These intermediaries encode item information that the robot's optical scanner can easily read and interpret, improving detection accuracy while keeping the overall system manageable in complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system enables efficient and automated tracking of physical objects, reducing manual effort and improving inventory management by accurately detecting absent items and triggering replenishment, thus enhancing supply chain efficiency.
Implementation Method 1
the autonomous robot device can detect via the optical scanner, at a first location along the shelf, a first machine-readable representation from the first set of machine-readable representations
Implementation Method 2
The autonomous robot device can include an inertial navigation system including an accelerometer and/or a gyroscope and can be configured to roam autonomously through the facility
Data Source
AI summary
Described in detail herein are methods and systems for detecting absent physical objects using autonomous robot devices. In exemplary embodiments, the system includes shelving units disposed throughout a facility storing sets of physical objects. A first set of machine readable representations can be disposed on the front surface of the shelving unit and a second set of machine readable representations can be disposed on the back wall of the shelving unit. The first and second set of machine readable representations can be encoded with identifiers associated with the sets of physical objects. An autonomous robot device can be configured to detect and read a first set of machine-readable representations in response to successfully detecting and reading the second set of machine readable representations the autonomous robot device can determine the absence of a set of like physical objects.