Method and apparatus for combining data to construct a floor plan
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Solution Overview
Problem
Autonomous robots face challenges in effectively mapping and navigating complex environments due to limitations in sensor integration, data processing, and user interaction, which hinders their ability to efficiently perform tasks like cleaning and navigation.
Innovation Solution
A robot configuration that includes a chassis, wheels, multiple sensors, a processor, and memory, capable of capturing and processing data to create a top-view model of the environment, allowing for intelligent path planning and user interaction through a smartphone application for task management and navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors are integrated to capture comprehensive environmental data, then the quality and completeness of environmental mapping is improved, but the device complexity and data processing burden increase
Solution Approach 1:
The patent combines data from multiple sensor types (LIDAR, cameras, depth sensors, wheel encoders) into a unified environmental model through integrated processing. The system merges point cloud data, image data, and odometry data to create a comprehensive map, resolving the contradiction by systematically integrating multiple sensors rather than using them independently.
Solution Approach 2:
The environmental model serves multiple functions simultaneously: navigation path planning, obstacle detection, cleaning task management, and user interaction interface. This multi-functionality justifies the complex sensor integration by demonstrating that the comprehensive data collection enables diverse operational capabilities from a single integrated system.
2Measurement precision
If comprehensive environmental data is collected and processed to create detailed models, then navigation and task planning accuracy is improved, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary environmental mapping and model creation during periods when the robot is stationary or moving slowly, preparing navigation paths and identifying cleaning tasks in advance. This allows the robot to make quick decisions during active navigation without real-time processing delays, resolving the contradiction between comprehensive analysis and rapid response.
3Extent of automation
If the robot autonomously creates and uses environmental models for navigation, then operational independence is improved, but the system complexity and difficulty of user interaction increase
Solution Approach 1:
The patent introduces a smartphone application as an intermediary between the autonomous robot and the user. The app provides simplified interfaces for users to view environmental models, plan cleaning tasks, and control robot operations without needing to understand the complex autonomous navigation systems. This mediator resolves the contradiction by shielding users from system complexity while maintaining full autonomous capability.
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
Enables the robot to autonomously navigate and perform tasks efficiently by creating a detailed environmental model, allowing for effective path planning and user interaction, enhancing its cleaning capabilities and overall operational efficiency.
Implementation Method 1
upon incidence of illumination light with an object in a path of the robot reflections of the illumination light fall within a field of view of the first sensor
Implementation Method 2
a light detection and ranging (LIDAR) sensor
Data Source
AI summary
A robot configured to perceive a model of an environment, including: a chassis; a set of wheels; a plurality of sensors; a processor; and memory storing instructions that when executed by the processor effectuates operations including: capturing a plurality of data while the robot moves within the environment; perceiving the model of the environment based on at least a portion of the plurality of data, the model being a top view of the environment; storing the model of the environment in a memory accessible to the processor; and transmitting the model of the environment and a status of the robot to an application of a smartphone previously paired with the robot.