System and method for radar based mapping for autonomous robotic devices
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Solution Overview
Problem
Current radar-based mapping techniques struggle to detect obstacles, especially transparent or reflective surfaces, and require large receiver arrays or mechanical scanning, limiting their effectiveness in indoor environments for mobile robots.
Innovation Solution
The use of radar reprojection techniques, which calculate the angle of detection by analyzing Doppler effects and phase differences between antenna signals, allowing for obstacle mapping without mechanical scanning and enabling detection of targets on both sides of the path, even in static environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If radar-based mapping techniques are used to detect obstacles, then detection capability is improved, but the ability to detect transparent or reflective surfaces deteriorates
Solution Approach 1:
The patent replaces mechanical scanning radar systems with an electronic reprojection method. Instead of physically moving the radar antenna to scan the environment, the system uses signal processing techniques (reprojection algorithms) to calculate obstacle positions based on Doppler effects and phase differences from a stationary multi-antenna array. This substitution enables detection of transparent and reflective surfaces that were previously undetectable by conventional radar, while eliminating mechanical complexity.
Solution Approach 2:
The patent employs a composite signal processing approach that combines multiple radar signals from different antennas, integrates Doppler effect analysis with phase difference measurements, and merges reprojection calculations with traditional range-finding methods. This composite technique creates a robust detection system that overcomes the limitations of individual methods, particularly for detecting challenging surfaces like glass and metal.
2Measurement precision
If large receiver arrays or mechanical scanning are used to improve mapping accuracy, then measurement precision is improved, but device complexity deteriorates
Solution Approach 1:
The patent eliminates mechanical scanning components by replacing them with an electronic reprojection algorithm. The system uses a stationary multi-antenna array combined with signal processing to achieve accurate mapping without any moving parts. This substitution maintains measurement precision while dramatically reducing device complexity and eliminating reliability issues associated with mechanical wear and failure.
Solution Approach 2:
The patent transitions from spatial scanning (mechanical movement in physical space) to mathematical reprojection (computational processing in signal space). By transforming the problem from a physical scanning task to a computational reprojection task, the system achieves the same mapping accuracy using a fixed antenna array, thereby reducing mechanical complexity while maintaining precision.
3Difficulty of detecting and measuring
If mechanical scanning is used to map the environment, then obstacle detection is improved, but the ability to detect targets on both sides of the path deteriorates
Solution Approach 1:
The patent divides the environment into multiple detection sectors, each monitored by a specific antenna in the array. By segmenting the spatial field and assigning different antennas to different angular sectors, the system achieves comprehensive coverage on both sides of the robot's path simultaneously, eliminating the sequential limitation of mechanical scanning while improving overall detection capability.
4Ease of manufacture
If conventional radar techniques are used, then simple implementation is achieved, but resolution and penetration depth deteriorate
Solution Approach 1:
The patent creates a composite signal processing system that integrates multiple radar techniques: Doppler effect analysis for motion detection, phase difference measurement for angular positioning, and reprojection algorithms for accurate range calculation. This composite approach combines the advantages of different methods to achieve superior resolution and penetration depth while maintaining implementation feasibility through systematic signal processing.
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
This approach enables accurate mapping and obstacle avoidance in indoor environments, improving the radar sensor's resolution and penetration depth, and allowing for efficient path planning and navigation without the need for elaborate receiver arrays or mechanical scanning.
Implementation Method 1
calculate the angle of detection by analyzing Doppler effects and phase differences between antenna signals
Implementation Method 2
calculate the angle of detection by analyzing Doppler effects and phase differences between antenna signals
Data Source
AI summary
Data from a radar sensor moving through a static environment may be smoothed and used to generate range profiles by approximating peaks. A direction of arrival (DOA) can then be determined based on the range profile in order to generate a reprojection map. The reprojection map is used to provide updates to a stored map in a robot.