Shopping Robot Arm Placement for Dense Aisle Item Collection
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Solution Overview
Problem
Shopping experiences in physical stores are hindered for elderly or disabled individuals due to the difficulty in reaching or handling items, and modern shopping methods require optimization for efficient in-store item collection.
Innovation Solution
A robot system with a robotic arm and sensors, including cameras, a processor, and a holding compartment, that autonomously collects and places items based on image data and handling instructions, optimizing storage within the compartment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If stores pack more items in aisles to reduce square footage, then product prices can be kept low, but items become harder to reach and collect
Solution Approach 1:
The robotic arm autonomously collects items from shelves and places them in the shopping cart without human intervention. The system independently navigates, identifies products, grasps items, and stores them, enabling self-service shopping that resolves the contradiction between high item density and ease of collection.
Solution Approach 2:
The patent replaces the mechanical human arm with an automated robotic arm equipped with sensors, cameras, and control systems. This substitution enables automated item collection in densely packed aisles, maintaining accessibility while allowing higher product density.
2Productivity
If automated robotic arm collects and places items, then shopping efficiency is improved, but device complexity increases
Solution Approach 1:
The robotic arm is designed with multi-functionality, integrating navigation, item identification, grasping, and placement capabilities in a single system. This universal design improves shopping efficiency while managing complexity by consolidating functions rather than adding separate systems.
Solution Approach 2:
The system uses image recognition technology and computer vision as intermediaries between the robotic arm and the physical items. This intermediary layer enables automated decision-making for item selection and placement, improving efficiency while abstracting the complexity of direct sensor-to-action control.
3Stability of the object's composition
If robotic arm autonomously places items in holding compartment, then item organization is optimized, but measurement and detection difficulty increases
Solution Approach 1:
The system employs continuous feedback loops where cameras and sensors monitor item placement in real-time, and the control system adjusts the robotic arm's movements accordingly. This feedback mechanism ensures accurate item organization while managing detection complexity through iterative correction.
Solution Approach 2:
The robotic arm pre-plans item placement locations based on item type, size, and compartment configuration before execution. This preliminary action optimizes organization by pre-determining optimal positions, reducing the complexity of real-time detection and adjustment during placement.
Data Source
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AI summary
A robot system includes a holding compartment configured to transport one or more items and an electronic control unit having a processor and a non-transitory computer readable memory including a machine-readable instruction set. The robot system further includes a camera for capturing image data of an environment of the holding compartment and a robotic arm each communicatively coupled to the electronic control unit. The machine-readable instruction set causes the processor to receive image data of the environment of the holding compartment from the camera, determine a set of handling instructions for an item collected by the robotic arm, determine a location within the holding compartment for placing the item collected by the robotic arm based on the image data of the environment of the holding compartment and the set of handling instructions, and manipulate the robotic arm to place the item within the holding compartment at the determined location.