Environmental Parameter Mapping for Noise-Robust Robot Navigation
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Solution Overview
Problem
Sensor fusion in navigation systems faces accuracy reduction due to bias from false readings, and existing methods do not effectively account for location-specific variations in sensor data, leading to suboptimal decision-making.
Innovation Solution
The method involves creating a mapping data structure that stores environmental parameters with location-specific measurements and variances, allowing for the interpolation of virtual measurements that reduce noise and improve accuracy by averaging nearby data points, and incorporating action-relevant data to enhance decision-making, such as determining when to perform actions like mowing grass based on height thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensor fusion is used to combine data from multiple sources, then accuracy and robustness are improved, but the system becomes more complex and computationally intensive
Solution Approach 1:
The patent segments the environment into discrete grid cells, with each cell containing sensor readings and virtual measurements. This segmentation allows the complex sensor fusion problem to be broken down into manageable local computations at each grid cell, reducing overall system complexity while maintaining navigation accuracy through localized processing.
Solution Approach 2:
The patent introduces virtual measurements as an intermediary layer between raw sensor readings and navigation decisions. These virtual measurements act as mediators that smooth out noise and outliers in the sensor data, providing a more reliable basis for navigation without requiring complex filtering algorithms.
2Measurement precision
If raw sensor readings are used directly for navigation decisions, then the system remains simple, but accuracy is reduced due to noise and false readings
Solution Approach 1:
The patent creates virtual measurements as copies of raw sensor readings, stored in a mapping data structure. These copied measurements can be processed and filtered independently from the original sensor data, allowing the system to maintain simple sensor acquisition while improving decision-making reliability through processed copies.
Solution Approach 2:
The patent transforms raw sensor readings into virtual measurements by changing their representation in the mapping data structure. This parameter change allows the system to filter out noise and outliers while preserving the essential information needed for reliable navigation decisions.
3Measurement precision
If location-specific sensor variations are accounted for, then navigation accuracy improves, but data processing complexity increases
Solution Approach 1:
The patent applies local quality by storing and processing sensor readings specific to each grid cell location. Each location in the mapping data structure has its own virtual measurements that reflect local environmental characteristics, allowing the system to account for location-specific variations without requiring global reprocessing of all data.
Data Source
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AI summary
A system and method for environmental parameter mapping. A method includes adding at least one entry to a mapping data structure, wherein each entry includes a position of a robotic device and at least one corresponding environmental parameter for the respective position of the robotic device, wherein each environmental parameter of each entry indicates an attribute of an environment at the corresponding position and is based on at least one sensor signal captured at the corresponding position; and sending at least one command to the robotic device, wherein the at least one command is determined based on the mapping data structure and includes at least one command to navigate.