Mobile Assist Mapping Using After-Time Object Position Prediction
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Solution Overview
Problem
Existing automatic travel systems create environment maps that are time-specific, making it difficult to effectively utilize object information from previous autonomous travels in current autonomous travels due to changes over time.
Innovation Solution
An assist system that includes a first mobile body with a detector and communicator to transmit object information and detection time, and a server that calculates an after-time outer end position using elapsed time or growth state to facilitate effective use of object information across different time periods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If environment maps are created for each autonomous travel, then the system can accurately represent the environment at the time of travel, but the object information cannot be effectively reused across different time periods due to changes in the environment
Solution Approach 1:
The system performs preliminary estimation of future object positions by calculating after-time outer end positions based on current object information and elapsed time. This preliminary calculation allows the system to prepare environment maps that account for future changes, enabling accurate navigation even when the environment has changed since the original detection.
Solution Approach 2:
The system changes the parameter of object position information by calculating after-time outer end positions that adjust current object positions based on elapsed time and growth rates. This parameter transformation allows object information to remain valid across different time periods despite environmental changes.
2Reliability
If the system uses current object information for navigation, then navigation accuracy is maintained, but the system cannot utilize historical object information from previous travels
Solution Approach 1:
The system incorporates feedback by using detected object information to calculate after-time outer end positions that predict future states. This feedback loop allows historical data to inform future navigation decisions, maintaining accuracy while utilizing past information effectively.
3Productivity
If the system creates new environment maps for each travel, then the environment representation is up-to-date, but redundant data processing is performed and historical data is wasted
Solution Approach 1:
Instead of discarding historical object information, the system recovers and utilizes it by calculating after-time outer end positions. The historical data is transformed into predictive information that can be used for future navigation, eliminating redundant processing while preserving valuable historical insights.
Data Source
AI summary
An assist system includes a first mobile body including a detector to detect objects in a surrounding area of the first mobile body, and a first communicator configured or programmed to transmit object information about an object detected by the sensor and detection time information indicating a detection time at which the object is detected, and a server including a calculator configured or programmed to calculate, based on the object information and the detection time information from the first mobile body, an after-time outer end position of the object in a time-of-use during which the object information is to be used, and a second communicator configured or programmed to transmit the after-time outer end position to the first mobile body or to a second mobile body.