Mobile Robot Signal Mapping for Indoor Localization Accuracy
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Solution Overview
Problem
There is a challenge in integrating the autonomous behavior of household mobile robots with IoT connectivity, particularly in navigating and mapping operating environments with varying conditions and sensor inputs.
Innovation Solution
A method of operating a mobile robot that involves receiving occupancy data and signal coverage data through localization sensors and wireless receivers, respectively, to generate a map indicating coverage patterns of wireless communication signals. This map can be used to determine the location of electronic devices and the mobile robot itself within the environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a mobile robot integrates multiple sensors and IoT connectivity for autonomous operation, then the robot's ability to navigate and map environments improves, but the device complexity and computational resource requirements increase
Solution Approach 1:
The patent combines data from multiple sensors (cameras, LIDAR, wireless signal receivers) and correlates this data with occupancy information to generate unified environmental maps. This merging of sensor inputs and data processing approaches enables comprehensive environmental understanding while managing system complexity through integrated architecture
Solution Approach 2:
The mobile robot is designed with multi-functional capabilities, using the same platform for both autonomous navigation tasks and wireless signal mapping. The robot's sensors and processors serve multiple purposes: navigation, environmental mapping, and characterizing wireless communication coverage, thereby reducing overall system complexity through shared resources
2Measurement precision
If the mobile robot collects and processes extensive localization and signal coverage data, then the accuracy of robot localization and electronic device location determination improves, but the loss of time for data processing increases
Solution Approach 1:
The system performs preliminary data collection and processing by generating occupancy maps and signal coverage maps in advance during robot navigation. This preliminary action allows the robot to build comprehensive environmental models before specific localization tasks are needed, reducing real-time processing requirements and time loss during critical operations
Solution Approach 2:
The patent implements feedback mechanisms where the robot continuously compares collected localization data and signal coverage data against generated maps, refining its position estimates and updating environmental models iteratively. This feedback loop improves localization accuracy over time while distributing processing load across multiple navigation cycles rather than requiring intensive single-step computation
Data Source
AI summary
A method of operating a computing device includes receiving occupancy data for an operating environment of a mobile robot based on localization data detected by at least one localization sensor of the mobile robot responsive to navigation thereof in the operating environment, and receiving signal coverage data for the operating environment based on wireless communication signals acquired by at least one wireless receiver of the mobile robot responsive to navigation thereof in the operating environment. The wireless communication signals are transmitted by at least one electronic device that is local to the operating environment. The method further includes generating a map indicating coverage patterns of the wireless communication signals at respective locations in the operating environment by correlating the occupancy data and the signal coverage data. Related methods, mobile robots, and user terminals are also discussed.