Multi-Sensor Merging for Super-Close Autonomous Navigation
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Solution Overview
Problem
Current space vision navigation technologies face challenges in detecting spatial position, orientation, and environmental information, especially at super-close distances, due to limited field angles, exploration ranges, and issues with shielding, which affect navigation precision and reliability.
Innovation Solution
A multi-sensor merging system combining infrared and visible light imaging sensors with laser distance measuring sensors, along with a sensor scanning structure and orientation guiding structure, to enhance field of view, data precision, and navigation efficiency, allowing for autonomous navigation within 200 meters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If monocular or binocular vision navigation is used for super-close distance navigation, then autonomous navigation capability is achieved, but field angle is limited and exploration range is restricted
Solution Approach 1:
The patent combines multiple sensor systems (optical imaging sensors, infrared imaging sensors, laser distance measuring sensors) into an integrated navigation system. This merging of sensors allows the system to overcome the limited field angle and exploration range of single-sensor systems while maintaining autonomous navigation capability at super-close distances.
Solution Approach 2:
The navigation system is designed with multi-functional sensors that can perform multiple tasks simultaneously. The optical and infrared imaging sensors capture visual and thermal information, while laser distance sensors provide range data, enabling the system to adapt to various navigation scenarios and extend its exploration range beyond what single-sensor systems can achieve.
2Reliability
If passive measurement mode is used for navigation, then autonomous navigation is achieved, but shielding problems occur and information is lost
Solution Approach 1:
The patent introduces active measurement sensors (laser distance measuring sensors) as intermediaries to complement the passive optical and infrared imaging sensors. These active sensors can penetrate shielding and provide distance information in conditions where passive sensors fail, thereby preventing information loss and improving navigation reliability.
Solution Approach 2:
By merging active and passive measurement modes into a unified navigation system, the patent creates a complementary measurement architecture. The active sensors provide information where passive sensors fail due to shielding, while passive sensors provide detailed visual and thermal information where active sensors are effective, together achieving comprehensive and reliable navigation.
3Measurement precision
If multiple sensors are combined to widen field of view and exploration range, then navigation precision is improved, but device complexity increases
Solution Approach 1:
The patent segments the sensor system into distinct functional modules: optical imaging sensors for visual information, infrared imaging sensors for thermal information, and laser distance measuring sensors for range information. Each module processes its specific type of data independently before fusion, which manages complexity while achieving high measurement precision through comprehensive spatial information.
Solution Approach 2:
The patent merges data from multiple sensor types through an information fusion process that integrates optical, infrared, and laser measurement data. This fusion approach achieves high measurement precision by combining complementary information from different sensors while managing system complexity through structured data processing and coordination.
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
The system effectively addresses limitations in existing navigation modes by providing comprehensive spatial information, improving navigation precision, safety, and reliability through the combination of sensors and scanning structures, enabling precise attitude adjustments and real-time data processing.
Implementation Method 1
first to fifth laser distance measuring sensors
Implementation Method 2
first and second infrared imaging sensors
Implementation Method 3
first and second visible light imaging sensors
Data Source
AI summary
The present invention discloses a multi-sensor merging based super-close distance autonomous navigation apparatus and method. The apparatus includes a sensor subsystem, an information merging subsystem, a sensor scanning structure, and an orientation guiding structure, wherein a visible light imaging sensor and an infrared imaging sensor are combined together, and data are acquired by combining a passive measurement mode composed of an optical imaging sensor and an active measurement mode composed of a laser distance measuring sensor. Autonomous navigation is divided into three stages, that is, a remote distance stage, implemented by adopting a navigation mode where a binocular visible light imaging sensor and a binocular infrared imaging sensor are combined, a close distance stage, implemented by adopting a navigation mode where a binocular visible light imaging sensor, a binocular infrared imaging sensor and a laser distance measuring sensor array are combined, and an ultra-close distance stage, implemented by adopting a navigation mode of a laser distance measuring sensor array. Through the present invention, the field of view and the exploration range are widened, the problem of shielding existing in passive measurement is effectively solved, the precision of data measurement is ensured, and the navigation efficiency and the safety and reliability of navigation are improved.