Relative Map Navigation for UGV Obstacle Avoidance Under INS Drift
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Solution Overview
Problem
Current navigation systems for unmanned ground vehicles (UGVs) face inaccuracies and drift issues with GPS and INS, leading to potential collisions with obstacles, especially in dense environments, and are unreliable where satellite communication is unavailable.
Innovation Solution
The system generates and updates a relative map of the environment using onboard scanning devices, integrating INS data to track the vehicle's position and avoid obstacles, with cell sizes selected to accommodate INS drift, allowing for accurate navigation without external references.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS is used for navigation, then the vehicle can obtain location information, but the location data becomes inaccurate and jittery
Solution Approach 1:
The patent introduces an intermediary mechanism (prediction module and buffer module) between GPS and the navigation system. The prediction module predicts the vehicle's location based on historical GPS data and INS data when GPS signals are unavailable or inaccurate, acting as a mediator to smooth out GPS jitter and fill gaps. This resolves the contradiction by maintaining navigation reliability while preserving the ability to use GPS location information when available.
Solution Approach 2:
The system performs preliminary actions by continuously buffering GPS location data and predicting future positions before actual navigation decisions are made. The buffer module stores historical GPS data, and the prediction module pre-calculates expected positions, so when GPS data is missing or inaccurate, the navigation system already has prepared alternative location information, thus maintaining accuracy and reliability.
2Adaptability or versatility
If INS is used for tracking vehicle position, then the vehicle can navigate without external references, but errors accumulate due to drift
Solution Approach 1:
The patent implements feedback by continuously comparing INS-derived position with GPS position when GPS is available. The system uses GPS to correct INS drift periodically, creating a feedback loop that resets accumulated errors. This allows the system to maintain independence from external references (using INS) while periodically recalibrating against GPS to prevent error accumulation, thus resolving the contradiction between independence and accuracy.
Solution Approach 2:
The system performs preliminary correction by using GPS data to predict and correct INS drift before it accumulates significant errors. The buffer module stores GPS data that is used in advance to establish correction patterns, allowing the system to maintain high position accuracy even when operating independently from external references for extended periods.
3Ease of operation
If GPS is used for navigation, then location information is obtained, but it fails when satellite communication is unavailable
Solution Approach 1:
The patent merges GPS-based navigation with INS-based navigation into a unified system. The navigation system can switch between or combine GPS data and INS data depending on availability. This merging allows the vehicle to operate in environments where GPS is unavailable (indoors, underground, in dense urban areas) while still maintaining navigation capability, thus expanding the operational environment range without losing ease of operation.
Solution Approach 2:
The prediction module acts as an intermediary that bridges GPS and INS navigation systems. When GPS is unavailable, the prediction module uses historical GPS data and INS data to maintain navigation capability, ensuring seamless transition between systems. This resolves the contradiction by maintaining ease of operation through automatic system switching while expanding adaptability to various operational environments.
4Measurement precision
If cell size in the map is made small to improve positioning precision, then collision risk increases due to INS drift
Solution Approach 1:
The patent makes the map structure dynamic by allowing the system to adaptively adjust to INS drift. The map is not static but is continuously updated and re-aligned based on the vehicle's actual position relative to detected obstacles. This dynamic approach allows the system to maintain small cell sizes for precision while compensating for INS drift through continuous map updates, thus preserving both positioning precision and collision avoidance reliability.
Solution Approach 2:
The system uses feedback from obstacle detection to correct map alignment errors caused by INS drift. When obstacles are detected, the system compares their expected positions (based on INS data) with actual detected positions, and uses this feedback to realign the map. This feedback mechanism allows the maintenance of small cell sizes for precision while automatically correcting drift-induced errors, ensuring collision avoidance reliability.
Data Source
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AI summary
The presently disclosed subject matter includes a system and a method of navigating a vehicle, the vehicle comprising a scanning device and a self-contained navigation system (SCNS) being operatively connected to a computer, the method comprising: operating the scanning device for repeatedly executing a scanning operation, where each scanning operation includes scanning an area surrounding the vehicle, to thereby generate respective scanning output data; operating the computer for generating, based on the scanning output data from multiple scanning operations, a relative map representing at least a part of the area, the relative map having known dimensions and being relative to a position of the vehicle, wherein the relative map comprises cells, each cell being classified to a class selected from at least two classes, comprising traversable and non-traversable, and characterized by dimensions equal or larger than an accumulated drift value of the SCNS over a predefined distance; wherein non-traversable cells correspond to obstacles identified in the scanning output data; receiving SCNS data and updating a position of the vehicle relative to the cells based on the SCNS data.