Swap Body Detection From Partial Point Clouds for Vehicle Docking
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Solution Overview
Problem
Existing technologies face challenges in detecting swap bodies in industrial environments due to incomplete or occluded sensor views, varying swap body dimensions and surfaces, and adverse environmental conditions like weather and dust. Additionally, the detection must be fast enough to assist real-time navigation for safe docking operations.
Innovation Solution
A method and system that utilize a fusion and labeling system with at least one sensor to analyze pointcloud data for detecting the front plane, side plane, and legs of a swap body. This system updates a model based on the detection and provides it to the vehicle's navigation system for assistance in navigating towards the swap body for docking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If sensors are used to detect swap body features in industrial environments, then detection capability is improved, but detection reliability deteriorates due to incomplete or occluded sensor views
Solution Approach 1:
The detection system segments the swap body into distinct geometric features (front plane, side plane, legs) and detects each segment separately using point cloud data. This segmentation allows the system to identify individual features even when the overall view is occluded, improving reliability while maintaining detection capability.
Solution Approach 2:
The patent introduces an intermediate processing layer that fuses sensor data with a geometric model of the swap body. This intermediary model acts as a mediator between raw sensor inputs and final detection outputs, allowing the system to infer occluded features based on the expected geometric structure, thereby improving detection reliability.
2Speed
If real-time processing is implemented to assist navigation, then response speed is improved, but measurement precision deteriorates due to simplified processing
Solution Approach 1:
The system performs preliminary actions by pre-defining the geometric model of the swap body with its expected features (front plane, side plane, legs). This preliminary structuring allows real-time processing to focus on matching sensor data against the predefined model rather than performing complete object recognition, maintaining both speed and precision.
Solution Approach 2:
The patent implements partial action by detecting only the critical geometric features (front plane, side plane, at least three legs) necessary for safe docking, rather than performing exhaustive analysis of all swap body characteristics. This selective detection maintains real-time processing speed while achieving sufficient precision for navigation safety.
3Measurement precision
If complete sensor data processing is performed, then detection accuracy is improved, but processing time increases
Solution Approach 1:
The system extracts and processes only the essential geometric features (front plane, side plane, legs) from the complete sensor data, discarding redundant information. This extraction approach maintains detection accuracy for critical docking features while significantly reducing processing time by avoiding analysis of non-essential data.
Solution Approach 2:
The patent applies partial action by performing detection only on the minimum necessary features (at least three legs, front plane, side plane) required for safe swap body identification and docking. This partial detection approach achieves sufficient accuracy for navigation while limiting processing time, avoiding exhaustive analysis of all possible swap body characteristics.
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 assists in the navigation and docking of vehicles with swap bodies by providing accurate and timely detection of swap body features, even in challenging environments, thereby enhancing safety and efficiency in industrial settings.
Implementation Method 1
a LIDAR sensor, based on the principle of emitting a lightwave beam, catching the reflections of objects (backscattering) in the field of view, and providing relative position information about reflecting objects
Data Source
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AI summary
A method and system are devised for detection of a target swap body (200) having a front plane (203), a side plane (204) and four legs, to be picked up by a vehicle (100) equipped with a fusion and labelling system and at least one sensor (101-105). When the vehicle reaches a first location within a range of the target swap body (A), a pointcloud formed from data provided by the at least one sensor is received from the fusion and labelling system and processed. If the front and the side plane of the target swap body are detected, a current model is created or updated for the target swap body. If the front plane and at least three of the four legs of the target swap body are detected, a current model is created or updated for the target swap body. The created or updated model is provided to a navigation system of the vehicle (100). Operations are repeated to assist the vehicle (100) navigate from the first location to a second location (C) enabling picking up the target swap body (200).