LiDAR Container Misalignment Detection for Autonomous Transport
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Autonomous vehicles face challenges in detecting container misalignment during transportation, which can lead to damage to containers, goods, and the vehicle itself, as human intervention is impractical due to safety concerns and limited visibility.
Innovation Solution
A container misalignment detection system using LiDAR scanning devices mounted on the autonomous vehicle to capture data points and determine height differences between designated points on the container, triggering an alarm if the difference exceeds a threshold, facilitating manual re-alignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual inspection methods are used to detect container misalignment, then human operators can visually assess alignment, but safety concerns and limited visibility make human intervention impractical
Solution Approach 1:
The patent replaces manual visual inspection with an automated LiDAR-based detection system. The LiDAR device emits laser beams to scan the container and vehicle, capturing spatial data points that are processed to determine alignment status. This substitution eliminates the need for human operators to physically approach and visually assess the container, resolving the contradiction between detection reliability and operational safety.
2Reliability
If automated LiDAR scanning is implemented to detect container misalignment, then detection capability is improved, but system complexity increases
Solution Approach 1:
The LiDAR device serves multiple functions: it scans both the container and the autonomous vehicle simultaneously, captures spatial data points from multiple locations, and provides comprehensive alignment detection. This multi-functionality reduces the need for separate sensing systems for different components, thereby improving detection capability while limiting the increase in overall system complexity.
3Measurement precision
If comprehensive data points are captured to ensure accurate alignment detection, then measurement precision is improved, but data processing complexity increases
Solution Approach 1:
The system extracts only the essential spatial data points from the comprehensive LiDAR scan that are relevant for alignment detection. By identifying and processing only the critical coordinates needed to determine misalignment, the system achieves high measurement precision while avoiding the computational burden of processing all captured data points, thus limiting data processing complexity.
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
Ensures proper container alignment for safe transport by automating the detection process, preventing damage and enhancing operational efficiency in the shipping industry.
Implementation Method 1
A scanning device mounted on the autonomous vehicle captures a plurality of data points in the vicinity of the container
Implementation Method 2
A scanning device mounted on the autonomous vehicle captures a plurality of data points in the vicinity of the container
Data Source
AI summary
Systems, methods, and computer program products are described herein for container misalignment detection for an autonomous vehicle. Misalignment of a container loaded onto an autonomous vehicle is detected by receiving data including an indication that the container is loaded onto the autonomous vehicle. A scanning device mounted on the autonomous vehicle captures a plurality of data points in the vicinity of the container. A misalignment detection module identifies a first data point of the plurality of data points and a second data point of the plurality of data points. The misalignment detection module evaluates a height difference between a height of the first data point and a height of the second data point. The misalignment detection module determines whether the container is misaligned on the autonomous vehicle based on the height difference. An indication of whether the container is misaligned is provided.