Automated Product Visual Acquisition System Using Robotic Manipulation
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Solution Overview
Problem
The e-commerce industry faces challenges in efficiently managing and updating product visuals and information for a large number of products, leading to increased costs and difficulties in expanding product offerings, especially for retailers with hundreds or thousands of products.
Innovation Solution
A computer-implemented platform and acquisition system that allows for the generation, management, and sharing of product visuals, utilizing network servers, robotic manipulators, and cameras to capture and transform product data into various visual formats, enabling remote ordering, data acquisition, and storage of product profiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual processes are used for creating and managing product content for large numbers of products, then customization and quality control can be maintained, but the process becomes more cumbersome and expensive
Solution Approach 1:
The system enables automatic product content generation where the product itself serves as the source of data. Sensors and cameras capture product characteristics automatically, and the system processes this data to generate content without human intervention, allowing the product to essentially create its own content
Solution Approach 2:
Manual mechanical processes for content creation are replaced with automated imaging systems, sensors, and computer vision algorithms. The system uses optical sensors, cameras, and automated processing to substitute human manual work in capturing and generating product content
2Productivity
If more products are added to expand product offerings, then business growth is achieved, but the cost and complexity of content management increases
Solution Approach 1:
The system creates a universal content generation platform that can handle multiple product types, categories, and formats through a single integrated system. The same infrastructure generates content for diverse products, eliminating the need for separate processes for each product line
Solution Approach 2:
The system creates digital copies and representations of physical products through automated imaging and sensing. These digital twins or virtual representations can be replicated, distributed, and managed efficiently without requiring physical handling or manual content creation for each instance
3Productivity
If automated systems are implemented for generating product visuals, then efficiency and cost-effectiveness improve, but the initial investment and system complexity increase
Solution Approach 1:
The automated content generation system is divided into separate functional modules: product capture subsystem, data processing subsystem, content generation subsystem, and distribution subsystem. Each module performs a specific function and can be independently optimized, maintained, and scaled
Solution Approach 2:
The system introduces an intermediate digital representation layer between the physical product and the final content output. Sensors and cameras capture physical product data, which is then processed into digital models that serve as intermediaries for generating various content formats, simplifying the overall transformation process
Data Source
AI summary
An example system may include an acquisition system including a robotic manipulator and a camera coupled to the robotic manipulator. The example system may further include one or more network servers storing program instructions that, upon execution by at least one processor of the one or more network servers, cause the one or more network servers to perform various operations. The operations may include: receiving, from a client application operating on a client device, a product visual order; generating a product profile corresponding to the product visual order in a product visual database; transmitting, to the acquisition system, acquisition instructions for acquiring product visual data indicative of the tangible product; transforming captured product visual data into a product visual of the tangible product; and storing the product visual in the product profile.