AI Navigation Mapping for Flexible Robot Pose Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing robot pose control systems lack flexibility and require specialized knowledge to adapt to manufacturing or warehousing process changes, are complex to use, and often need integration with third-party systems, failing to consider alterations in room layout or robot equipment.
Innovation Solution
A system and method utilizing a navigation map creation module with AI algorithms to simplify user interaction, allowing quick adaptation to room alterations, and a user-friendly interface for inputting data, along with a third-party integration module for seamless integration with warehouse or manufacturing control systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing robot pose control systems are used, then robot positioning can be achieved, but the systems lack flexibility and require specialized knowledge to adapt to manufacturing or warehousing process changes
Solution Approach 1:
The system automatically detects and adapts to room alterations using sensors and AI algorithms without requiring user intervention or specialized knowledge. The navigation map creation module autonomously processes sensor data to update the navigation map, enabling the system to serve itself in adapting to changes.
Solution Approach 2:
The system proactively detects room alterations before they affect robot operations by continuously monitoring the environment with sensors. The AI algorithms process this data in advance to update the navigation map, preparing the system for upcoming changes rather than reacting after problems occur.
2Adaptability or versatility
If existing navigation map creation methods are used, then robot navigation can be established, but the systems are complex to use and often require integration with third-party control systems
Solution Approach 1:
The system provides multiple functions within a single integrated platform: sensor data acquisition, AI-based navigation map creation, robot pose control, and third-party system integration. This multi-functional approach eliminates the need for separate systems and reduces overall complexity while maintaining versatility.
Solution Approach 2:
The AI-based navigation map creation module serves as an intermediary that standardizes communication between diverse sensors and robot control systems. It processes various sensor data formats and converts them into a unified navigation map format, simplifying integration with third-party systems.
3Measurement precision
If detailed data about room alterations is captured, then positioning accuracy can be improved, but the amount of data to be processed increases
Solution Approach 1:
The system replaces complex manual data processing with AI-based automatic processing. The AI algorithms autonomously analyze sensor data, detect room alterations, and update the navigation map without requiring manual intervention, thereby maintaining high positioning accuracy while reducing processing complexity.
Solution Approach 2:
The system implements continuous feedback loops where sensors monitor room conditions, AI algorithms process the data to detect alterations, and the navigation map is updated accordingly. This closed-loop feedback mechanism ensures high positioning accuracy while automating the data processing workflow.
Data Source
AI summary
A group of inventions relates to a field of robotic engineering, in particular, to a system and a method for controlling a robot pose in a room, e.g., in a storage room when using robots for moving various storage containers.A system for controlling a robot pose in a room is provided, the system comprises a navigation map creation module for creating a navigation map that corresponds to an interior of the room and is for at least one robot that is configured to alter its pose in the room according to the created navigation map, a location control module for controlling a location of at least one robot in the room, the module is configured to receive a data from markers located in the room according to the created navigation map, as well as a data received by at least one sensor mounted in the robot upon its interaction with at least one marker, and a user-system interaction module that is configured to enable an interaction between a user and the navigation map creation module and the location control module for controlling the location of at least one robot in the room, wherein the navigation map creation module is configured to receive an input data about the room from the user via the user-system interaction module, to process the received data and to create a navigation map based on results of this processing using artificial intelligence (AI) algorithms. Also, a control of the robot pose in the room is provided.