Environmental Parameter Mapping for Bias-Resistant 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 utilize location-specific tracking of sensor readings to improve accuracy.
Innovation Solution
The method involves creating a mapping data structure that stores environmental parameters at specific locations, allowing for the identification and exclusion of deviating measurements, and using virtual measurements based on nearby readings to enhance navigation accuracy, while also incorporating action-relevant data for decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensor fusion is used to combine data from multiple sources, then accuracy and robustness are improved, but false readings from individual sensors can introduce bias that reduces overall accuracy
Solution Approach 1:
The system performs preliminary mapping of environmental parameters at various locations before navigation decisions are made. By pre-establishing a mapping data structure that stores expected environmental conditions at different positions, the system can compare real-time sensor readings against these pre-recorded values to identify and exclude false readings before they bias the navigation solution.
Solution Approach 2:
The system implements feedback by continuously comparing current sensor readings with historical environmental parameter data stored in the mapping data structure. This feedback mechanism allows the system to detect deviations caused by false readings and correct for them, thereby maintaining measurement precision while benefiting from sensor fusion.
2Measurement precision
If more sensor data is collected and processed, then navigation accuracy improves, but computational resources and energy consumption increase
Solution Approach 1:
The system extracts only the essential environmental parameters that are most relevant for navigation accuracy from the full sensor dataset. By identifying and storing only these critical parameters in the mapping data structure (such as key environmental characteristics at different locations), the system reduces the volume of data that needs to be processed while maintaining navigation accuracy.
Solution Approach 2:
The system applies local quality by creating location-specific environmental parameter profiles rather than processing all sensor data uniformly. Each position in the mapping data structure contains only the environmental parameters relevant to that specific location, allowing the system to process minimal data locally while achieving global navigation accuracy through aggregation of these localized profiles.
3Measurement precision
If environmental parameters are mapped at multiple locations, then navigation accuracy improves, but data storage requirements and processing complexity increase
Solution Approach 1:
The system segments the environment into discrete locations or zones, each with its own environmental parameter profile stored in the mapping data structure. By dividing the continuous environment into manageable segments, the system can store and process environmental data in a structured, organized manner that reduces overall complexity while maintaining comprehensive coverage for accurate navigation.
Solution Approach 2:
The mapping data structure is designed with universality to serve multiple functions: storing environmental parameters, enabling false reading detection, providing feedback for correction, and supporting navigation decisions. This multi-functional design consolidates what could be multiple separate systems into a single unified structure, reducing overall device complexity while achieving multiple objectives.
Data Source
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.