3D Model-Guided Robot Search for Shared Article Finding
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Solution Overview
Problem
People often struggle to find specific articles, such as books or keys, due to forgetfulness or poor organization, and existing solutions lack efficiency in assisting with this task.
Innovation Solution
A method and apparatus that utilize a 3D model of the article to be searched, combined with a search task group of robots, to efficiently locate the article by receiving a search task, acquiring a 3D model, determining a search task group, and searching based on the model and group, with shared search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a single robot performs the search task, then the device complexity is low, but the search efficiency and probability of finding the article are insufficient
Solution Approach 1:
The search task is divided into multiple sub-tasks performed by different robots in the search task group. Each robot searches in different regions or uses different search strategies, thereby increasing the overall search efficiency and probability of finding the article while distributing the complexity across multiple simpler agents.
Solution Approach 2:
Multiple robots are combined into a search task group that works collaboratively to complete the search task. The robots share search results and coordinate their actions, merging their individual capabilities to achieve higher productivity than a single robot could accomplish alone.
2Productivity
If multiple robots are deployed to search, then the search efficiency improves, but the system complexity and resource consumption increase
Solution Approach 1:
The search task group is designed with universal protocols for communication and coordination that can be applied across different search scenarios. Each robot in the group can perform multiple search functions and adapt to different search requirements, reducing the need for specialized complex systems for each individual robot.
Solution Approach 2:
The search task group implements feedback mechanisms where robots share search results and status information in real-time. This feedback allows the group to coordinate their actions dynamically, avoiding redundant searches and optimizing resource allocation, thereby managing system complexity while maintaining high productivity.
3Measurement precision
If traditional search methods are used, then the system is simple, but the search accuracy and user experience are poor
Solution Approach 1:
The system creates a digital representation or model of the search environment and article locations. By using copied information from sensors and shared memory, the search task group can accurately track and locate articles without requiring complex physical manipulation or direct observation by each robot, thereby improving accuracy while managing system complexity.
Data Source
AI summary
An article searching method includes: receiving a search task for searching for an article to be searched; acquiring, based on the search task, a three dimensional model corresponding to the article to be searched; determining a search task group for searching for the article to be searched; and searching for the article to be searched based on the acquired three dimensional model and in combination with the search task group, wherein the search task group shares a search result in the process of searching for the article to be searched.