Adaptive Localization Uncertainty for Dynamic Environment Mapping
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Solution Overview
Problem
Existing robotics navigation systems fail to account for dynamic environments, leading to localization uncertainties due to moving objects and changes in the environment, which can result in localization failures and unsafe motion planning.
Innovation Solution
A method to determine localization uncertainty levels (LUL) by considering both static and dynamic elements in the environment, using sensor data and map information to adapt LUL based on dynamicity levels, ensuring robustness against environmental changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional localization methods are used in static environments, then localization precision is high, but reliability deteriorates when dynamic elements are present
Solution Approach 1:
The patent changes the parameter of localization uncertainty by introducing dynamicity level assessment. The system computes LUL_new by adjusting the base LUL based on the dynamicity level D_map of environmental elements, transforming the static localization uncertainty metric into a dynamic one that adapts to environmental changes, thereby maintaining reliability in dynamic settings
Solution Approach 2:
The patent applies dynamics by making the localization uncertainty level adaptive rather than static. The system continuously updates LUL based on real-time detection of dynamic elements (people, machines, boxes) and their movement, allowing the localization system to dynamically adjust its uncertainty assessment according to environmental conditions
2Reliability
If the system accounts for dynamic elements in localization, then reliability improves, but device complexity increases
Solution Approach 1:
The patent segments the environmental elements into static and dynamic categories, assigning different handling procedures to each. By classifying elements based on their dynamicity level D_map, the system processes only relevant dynamic elements for localization uncertainty adjustment, avoiding the complexity of analyzing all environmental elements equally
Solution Approach 2:
The patent applies local quality by computing dynamicity levels specifically for portions of the map where dynamic elements are detected, rather than uniformly processing the entire environment. The LUL adjustment is localized to areas affected by dynamic elements, reducing overall computational complexity while maintaining reliability
3Measurement precision
If localization uncertainty is computed without considering dynamicity, then computational efficiency is high, but localization accuracy deteriorates in dynamic environments
Solution Approach 1:
The patent applies partial action by computing dynamicity levels only for portions of the environment where dynamic elements are detected, rather than analyzing the entire map. The LUL adjustment is applied selectively to affected regions, achieving improved localization accuracy without the computational cost of exhaustive analysis
Solution Approach 2:
The patent performs preliminary classification of environmental elements into static and dynamic categories before computing localization uncertainty. By pre-identifying dynamic elements and their locations, the system prepares the data structure needed for efficient LUL computation, avoiding redundant processing during the actual localization task
Data Source
AI summary
A first device can determine a map of an environment that includes a plurality of elements. The first device can further determine a localization uncertainty level (“LUL”) within the map. The first device can further determine a dynamicity level (“D_map”) for a portion of the plurality of elements in the map. The first device can further determine a new LUL (“LUL_new”) based on the LUL and the D_map. The first device can further provide the LUL_new to a second device in the environment.