SLAM Map Relocation Using Hybrid Position and Azimuth Tracking
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Solution Overview
Problem
Current SLAM technology struggles with accurately relocating mobile vehicles in complex or dynamically changing environments, leading to potential loss of positioning and map invalidation.
Innovation Solution
A method that employs both SLAM and non-SLAM positioning devices to detect position and azimuth trajectories, calculate loss probability, and update the SLAM map when conditions are met, ensuring accurate relocation of mobile vehicles by integrating trustworthiness values and continuous/discontinuous timestamp considerations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If SLAM technology is used to locate mobile robot position and draw map, then positioning function is provided, but in complex environments or when environment changes greatly, the mobile robot may get lost and positioning accuracy deteriorates
Solution Approach 1:
The patent combines SLAM positioning with non-SLAM positioning (GPS/Beidou) to create a hybrid positioning system. When SLAM positioning reliability is sufficient, it uses SLAM data; when reliability drops below threshold, it switches to non-SLAM positioning, thereby maintaining positioning precision and reliability in complex environments
Solution Approach 2:
The system continuously monitors SLAM positioning reliability and uses this feedback to dynamically switch between SLAM and non-SLAM positioning modes. This feedback mechanism ensures that positioning precision is maintained by selecting the appropriate positioning source based on real-time reliability assessment
2Adaptability or versatility
If only SLAM positioning device is used to establish and update SLAM map, then map building function is provided, but in complex or dynamically changing environments, the map becomes invalid and relocation fails
Solution Approach 1:
The patent merges SLAM map building with non-SLAM positioning data to create a more reliable positioning system. By combining data from both sources and using reliability thresholds, the system maintains map reliability and environmental adaptability even in complex or dynamically changing environments
3Extent of automation
If SLAM positioning is used to maintain position data, then autonomous navigation is enabled, but when environment changes greatly, the previously created map and positioning information become completely invalid
Solution Approach 1:
The system implements feedback by continuously evaluating SLAM positioning reliability and automatically switching to non-SLAM positioning when reliability drops below threshold. This maintains autonomous navigation capability while ensuring positioning information reliability in changing environments
Solution Approach 2:
The patent makes the positioning system dynamic by allowing automatic switching between SLAM and non-SLAM positioning modes based on real-time reliability assessment. This dynamic adaptation preserves autonomous navigation while maintaining information reliability throughout environmental changes
Data Source
AI summary
A method for relocating a mobile vehicle in a simultaneous localization and mapping (SLAM) map is provided. The method can be used in the mobile vehicle moving in an area and includes: using SLAM to establish the SLAM map that corresponds to the area at an initial time point; detecting, by a non-SLAM positioning device, a first position trajectory and a first azimuth trajectory of the mobile vehicle on the SLAM map; detecting, by a SLAM positioning device, a loss probability of the mobile vehicle between a first timestamp and a second timestamp; determining whether a condition is satisfied; and updating the SLAM map to a new SLAM map corresponding to a current time point and updating positioning information of the mobile vehicle in the new SLAM map when the condition is satisfied at the current time point.