Dynamic Range Adjustment for Mobile Position Estimation
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Solution Overview
Problem
Conventional own position estimation techniques face difficulties in accurately estimating the position of a mobile body when movement amount detection errors increase, leading to significant deviations between sensing results and map data.
Innovation Solution
The system detects landmark positions using cameras and laser rangefinders, accumulates landmark position data based on movement amounts, and adjusts the data extraction range based on estimated movement detection errors to match the data with map information, thereby stabilizing position estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If records of sensing results acquired within a fixed distance are used for position estimation, then stable position estimation is achieved by eliminating influence of mobile body movement speed, but deviation between sensing results and map increases significantly when movement amount detection error increases
Solution Approach 1:
The patent applies dynamics by making the data extraction range variable rather than fixed. The range is dynamically adjusted based on the detected movement amount and estimated detection error. When movement error is small, a larger range is used to maintain stability; when movement error is large, a smaller range is used to maintain accuracy. This dynamic adaptation resolves the contradiction between stability and precision.
Solution Approach 2:
The patent changes the parameter of data extraction range based on movement detection error. By estimating the detection error and adjusting the extraction range accordingly, the system adapts its operation parameters to maintain both stability and accuracy under varying conditions. This parameter change allows the system to optimize performance based on real-time error conditions.
2Productivity
If a fixed data extraction range is used, then computation is simplified and processing is faster, but position estimation accuracy deteriorates when movement detection error increases
Solution Approach 1:
The system dynamically adjusts the data extraction range based on movement detection error, allowing it to optimize between processing speed and accuracy. When error is small, a larger range enables faster processing with sufficient accuracy; when error is large, a smaller range maintains accuracy despite increased processing. This dynamic adjustment resolves the contradiction between productivity and precision.
3Reliability
If landmark position data from a large range is extracted, then more data is available for matching improving estimation stability, but the influence of movement detection error increases leading to larger deviation from map data
Solution Approach 1:
The patent changes the extraction range parameter based on detected movement and estimated error. By adjusting this parameter dynamically, the system extracts an optimal amount of landmark data that provides sufficient stability while limiting the accumulation of deviation from map data. This parameter adaptation resolves the contradiction between having enough data for stability and avoiding excessive error accumulation.
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
This approach allows for accurate and stable own position estimation even with high movement detection errors by dynamically adjusting the data extraction range, reducing odometry errors and improving positional accuracy.
Implementation Method 1
sensing surroundings of the mobile body with a camera
Implementation Method 2
laser rangefinder mounted in the mobile body
Data Source
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AI summary
An own position estimation device of the present invention detects a landmark position of a landmark existing around a mobile body, detects a movement amount of the mobile body, and accumulates, as pieces of landmark position data, landmark positions each obtained by moving the detected landmark position by the movement amount. The device then acquires map information including landmark positions of landmarks existing on a map by the controller, matches the pieces of landmark position data in a certain range with the landmark positions included in the map information, and estimates the own position of the mobile body, the certain range being set based on movement records of the mobile body traveling to a current position.