Real-Time Load-Carrier Pose Estimation From Oblique Angles
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Solution Overview
Problem
Current Load-carrier Pose estimation systems are limited by sensor type-specific processing steps, struggle with wider range and oblique observation angles, and fail to uniquely identify multiple Load-carriers, necessitating rigid positioning systems.
Innovation Solution
A system combining 2D and 3D sensors with 2D Keypoint detection and 3D matching, utilizing a 3D template matching optimization initialized by initial Pose estimation, enabling real-time Pose estimation even with relative motion between vehicle and Load-carrier.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional sensor-specific processing steps are used, then the system can detect Load-carrier Pose, but it is limited to specific sensor types and requires rigid positioning systems
Solution Approach 1:
The patent applies universality by creating a unified Pose estimation system that works across multiple sensor types (2D cameras, 3D lidars, depth cameras) through a common architecture. The system uses a standardized workflow of detection, segmentation, and Pose estimation that can process data from different sensor modalities without requiring sensor-specific processing pipelines, making the system multi-functional and adaptable to various sensor configurations
Solution Approach 2:
The patent applies segmentation by dividing the Pose estimation process into distinct modular stages: Load-carrier detection, segmentation of Load-carrier data points from background, and Pose estimation. This segmented approach allows each module to be optimized independently for different sensor types while maintaining overall system coherence, reducing the complexity of handling multiple sensor types uniformly
2Measurement precision
If rigid positioning systems are used, then Load-carrier Pose can be determined accurately, but vehicle maneuvering flexibility is reduced
Solution Approach 1:
The patent applies dynamics by enabling real-time Pose estimation that adapts to dynamic conditions during vehicle maneuvering. The system continuously updates Load-carrier detection and Pose estimation as the vehicle moves, allowing flexible maneuvering without requiring rigid pre-positioning. The real-time processing capability maintains measurement precision while accommodating dynamic operational scenarios
3Device complexity
If 2D sensor data alone is used, then processing is simpler, but Pose estimation from wider range and oblique angles is limited
Solution Approach 1:
The patent applies merging by combining 2D sensor data (from cameras) with 3D sensor data (from lidars or depth cameras) to achieve accurate Pose estimation. The system integrates detection results from 2D images with depth information from 3D sensors, allowing Pose estimation from wider ranges and oblique angles while maintaining processing efficiency through the unified modular architecture
Data Source
AI summary
A system for Load-carrier Pose estimation. The system includes a Load-carrier for supporting a load with Load-carrier handling indicators or Key-points, and a driving vehicle. The Pose represents a relative position and orientation of the Load-carrier with reference to the vehicle. The system includes a 2D sensor and a 3D sensor. The system is arranged to detect 2D Keypoints in images of the Load-carrier obtained with the 2D sensor, and to match these 2D Keypoints with 3D data captured with the 3D sensor to establish a 3D position and orientation of the detected Keypoints.