Multi-Sensor Environmental Mapping for Accurate UAV Navigation
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Solution Overview
Problem
Existing approaches for obtaining environmental data by unmanned aerial vehicles (UAVs) are often inaccurate, which can negatively impact their functionality, especially in diverse environments and operating conditions.
Innovation Solution
The use of a combination of different sensor types, such as GPS, vision, and proximity sensors, to generate detailed environmental maps, including obstacle occupancy information, enabling improved navigation and obstacle avoidance capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single sensor type is used to collect environmental data, then the device complexity is reduced, but the measurement precision and reliability of environmental data deteriorate
Solution Approach 1:
The patent combines multiple sensor types (GPS receiver, vision sensor, and proximity sensor) into a unified sensor system that collects environmental data simultaneously. This merging of different sensing modalities resolves the technical contradiction by achieving high measurement precision through multi-sensor fusion while managing device complexity through integrated system architecture.
2Reliability
If multiple sensor types are used to generate detailed environmental maps, then the measurement precision and reliability improve, but the device complexity increases
Solution Approach 1:
The patent merges GPS, vision, and proximity sensors into a coordinated multi-sensor system that generates reliable environmental maps through data fusion. This combining approach achieves high reliability in environmental mapping while controlling device complexity through unified system management and integrated processing.
Solution Approach 2:
The sensor system is designed with multi-functionality, where each sensor type serves multiple purposes: GPS provides location data for navigation, vision sensors detect obstacles and map environments, and proximity sensors provide supplementary spatial information. This universal design enables reliable environmental mapping while optimizing device complexity by making each sensor component serve multiple functions within the integrated system.
Data Source
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AI summary
Systems and methods for controlling a movable object within an environment are provided. In one aspect, a method may comprise: determining, using at least one of a plurality of sensors carried by the movable object, an initial location of the movable object; generating a first signal to cause the movable object to navigate within the environment; receiving, using the at least one of the plurality of sensors, sensing data pertaining to the environment; generating, based on the sensing data, an environmental map representative of at least a portion of the environment; receiving an instruction to return to the initial location; and generating a second signal to cause the movable object to return to the initial location, based on the environmental map.