Autonomous Robot Under Vehicle Inspection
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Solution Overview
Problem
Entities with fleets of vehicles face challenges in efficiently maintaining, analyzing, and improving vehicle performance due to the high costs and time-consuming nature of manual inspections and data gathering.
Innovation Solution
A robotic vehicle inspection system comprising a home base, a robot with sensors capable of passing under vehicles, and a computer for analyzing sensor data and sending alerts, which automates the inspection process and facilitates data analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual vehicle inspection is performed, then inspection thoroughness is maintained, but inspection cost and time consumption increase significantly
Solution Approach 1:
The patent replaces manual mechanical inspection with an automated robotic system equipped with sensors, cameras, and computer vision algorithms. The robot autonomously navigates under vehicles, captures images and sensor data, and uses machine learning models to detect issues, eliminating the need for human inspectors while maintaining inspection quality.
Solution Approach 2:
The inspection system performs self-diagnosis and self-analysis through onboard sensors and embedded computing resources. The robot independently processes sensor data, compares it against learned patterns, and generates inspection reports without requiring external human intervention, enabling the system to serve itself in the inspection process.
2Extent of automation
If fixed camera installations are used for vehicle inspection, then automation is achieved, but system flexibility and upgradeability decrease
Solution Approach 1:
The patent employs a dynamic, mobile robotic platform instead of fixed installations. The robot can move to different locations, adjust its sensor orientations, and adapt its inspection path based on real-time conditions. This dynamic architecture allows the system to be easily reconfigured, upgraded, or relocated without permanent infrastructure changes.
Solution Approach 2:
The robotic inspection system is designed with multiple sensors (cameras, LIDAR, gas detectors, temperature sensors) and interchangeable end effectors that can perform various inspection tasks. The same platform can inspect different vehicle types, detect multiple defect types, and even perform minor maintenance tasks, making it a universal inspection solution rather than a single-purpose fixed system.
3Measurement precision
If comprehensive sensor data is collected from vehicles, then diagnostic accuracy improves, but data processing complexity and cost increase
Solution Approach 1:
The patent divides the data processing task into segmented stages: onboard preprocessing filters and organizes raw sensor data, edge computing nodes perform initial analysis and feature extraction, and cloud-based systems conduct comprehensive pattern recognition and diagnostic reasoning. This segmentation reduces the computational burden at each stage while maintaining overall diagnostic accuracy.
Solution Approach 2:
The system performs preliminary data filtering, validation, and feature extraction at the edge devices before transmitting data to central systems. By pre-processing data locally and only transmitting relevant findings or compressed feature sets, the system reduces data volume and processing complexity downstream while preserving diagnostic information quality.
Data Source
AI summary
Techniques for inspecting a vehicle using a robot and a home base configured to be situated on a vehicle lot are presented. The robot has a vertical dimension that permits the robot to pass under a vehicle on the vehicle lot. The robot includes at least one sensor and is configured to perform actions including: receiving charging at the home base; traversing a distance from the home base to a vehicle present on the vehicle lot; determining an identification of the vehicle; passing under the vehicle; and obtaining sensor data regarding the vehicle. A computer in communication with the robot is configured to perform actions including: receiving the identification of the vehicle and the sensor data from the robot; analyzing the sensor data based on at least comparison data; determining, based on the analyzing, to send an alert regarding the vehicle; and sending the alert regarding the vehicle.