LIDAR Radar Sensor Fusion for Occluded Object Detection
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Solution Overview
Problem
Current object detection methods using LIDAR and radar sensors face challenges in accurately detecting partially occluded objects due to sensitivity to light changes, limited search range, and processing time, especially at night, and struggle to maintain high detection accuracy.
Innovation Solution
A method and apparatus that combine LIDAR and radar sensors to collect data, extract objects, generate shadow regions, set regions of interest (ROI) based on object movement and reflectivity, and verify object presence by comparing overlapping ROIs, reducing processing time and operation amount.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If LIDAR sensor is used for object detection, then detection accuracy is improved, but processing time increases and detection reliability deteriorates under varying light conditions
Solution Approach 1:
The patent segments the detection process by dividing the search space into multiple ROIs and processing them in parallel. The processor divides received sensor data into multiple regions of interest and processes each region simultaneously, reducing overall processing time while maintaining detection accuracy.
Solution Approach 2:
The patent applies partial action by selectively processing only relevant regions rather than the entire search space. By identifying and processing only ROIs containing potential objects, the system reduces processing time and computational resources while maintaining detection accuracy for critical areas.
2Measurement precision
If LIDAR and camera are combined for object detection, then detection accuracy is improved, but device complexity increases and processing time increases
Solution Approach 1:
The patent merges LIDAR and radar sensors into a unified detection system that processes data from both sensors simultaneously. The processor integrates data from multiple sensor types to improve detection accuracy while managing system complexity through coordinated processing.
Solution Approach 2:
The patent creates a multi-functional detection system that can handle both LIDAR and radar data through a single processing framework. The processor is designed to universally process data from different sensor types, reducing overall system complexity despite using multiple sensor technologies.
3Productivity
If ROI processing is applied to reduce processing time, then productivity is improved, but detection precision may deteriorate for partially occluded objects
Solution Approach 1:
The patent performs preliminary actions by pre-identifying and marking ROIs before detailed processing. The system preliminarily scans the search space to identify potential object locations, then focuses detailed processing only on these pre-identified regions, ensuring neither processing speed nor detection accuracy is compromised.
Solution Approach 2:
The patent adds temporal dimension to ROI processing by performing multiple processing passes. The system processes ROIs in different time stages, including initial identification and subsequent verification passes, which improves detection accuracy for occluded objects while maintaining overall processing efficiency.
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 effectively detects partially occluded objects with reduced processing time and operation amount, improving detection accuracy and robustness, especially at night, by utilizing the strengths of both LIDAR and radar sensors.
Implementation Method 1
a light detection and ranging (LIDAR) sensor may have difficulty recognizing a color of a target to be detected
Implementation Method 2
light detection and ranging (LIDAR) sensor
Implementation Method 3
a radar sensor may be unable to classify a color and a type of a target
Implementation Method 4
reflectivity depending on a range and a movement speed of a moving object
Data Source
AI summary
Provided is an object detecting method and apparatus using a light detection and ranging (LIDAR) sensor and a radar sensor, the method may include collecting LIDAR data and radar data associated with a search region in which objects are to be found using the LIDAR sensor and radar sensor, extracting each of objects present within the search region based on the collected LIDAR data and radar data, generating shadow regions of objects extracted through the LIDAR sensor and setting an ROI of LIDAR sensor based on the extracted objects, setting an ROI of radar sensor based on a reflectivity depending on a range and a movement speed of moving object among the objects extracted through the radar sensor, comparing the ROI of the LIDAR sensor to the ROI of the radar sensor, and verifying whether the moving object is present based on a result of the comparing.