Mobile Fleet Maintenance Robot for Autonomous Vehicle Inspection
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Solution Overview
Problem
Commercial fleet vehicle operators face challenges in efficiently performing maintenance tasks such as visual inspections and maintenance operations, especially with the rise of electric vehicles, as drivers are often specialized technicians and maintenance requires significant time and resources.
Innovation Solution
Deployment of autonomous robots equipped with sensors, actuators, and modular platforms for navigation, inspection, and maintenance tasks, including tire pressure adjustment, charging, and other operations, utilizing SLAM for mapping and neural networks for object detection, enabling autonomous operation and data-driven maintenance decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If drivers perform visual inspection and maintenance tasks, then vehicle maintenance can be conducted, but driver time and operational efficiency are reduced
Solution Approach 1:
The system enables vehicles to perform self-inspection through onboard sensors and cameras that automatically detect damages, tire pressure issues, and other maintenance needs without human intervention. The vehicle essentially inspects itself, freeing drivers from these tasks.
Solution Approach 2:
Manual inspection and maintenance tasks performed by drivers are replaced by an automated robotic inspection system with sensors, cameras, and computer vision algorithms that conduct visual inspections, tire pressure checks, and maintenance assessments autonomously.
2Reliability
If specialized technicians perform maintenance tasks, then maintenance quality improves, but operational costs and time requirements increase
Solution Approach 1:
The system enables vehicles to perform self-inspection through onboard sensors and cameras that automatically detect damages, tire pressure issues, and other maintenance needs without human intervention. The vehicle essentially inspects itself, freeing drivers from these tasks.
Solution Approach 2:
The system continuously collects data from sensors, cameras, and vehicle systems, processes this information through computer vision and machine learning algorithms, and provides real-time feedback about vehicle condition. This automated feedback loop ensures consistent maintenance quality without requiring specialized technician intervention for routine inspections.
3Ease of manufacture
If manual inspection methods are used, then implementation is simple, but inspection accuracy and detection precision are limited
Solution Approach 1:
Manual inspection and maintenance tasks performed by drivers are replaced by an automated robotic inspection system with sensors, cameras, and computer vision algorithms that conduct visual inspections, tire pressure checks, and maintenance assessments autonomously.
Solution Approach 2:
The system creates digital copies and models of vehicle conditions through photogrammetry and 3D scanning, generating detailed virtual representations of the vehicle exterior and interior. These digital models can be analyzed with high precision to detect damages, measure dimensions, and track changes over time without physical contact with the vehicle.
4Reliability
If comprehensive maintenance tasks are performed, then vehicle readiness improves, but time required for maintenance increases
Solution Approach 1:
The system performs inspections and identifies maintenance needs during vehicle downtime or between uses, completing comprehensive checks before the vehicle is needed again. This preliminary action ensures vehicles are ready for use without requiring time-consuming maintenance interventions when needed.
Solution Approach 2:
The system enables continuous monitoring and inspection capabilities that operate whenever the vehicle is parked or not in use, turning otherwise idle time into productive maintenance windows. This allows comprehensive maintenance tasks to be performed continuously during downtime without affecting vehicle availability when needed.
Data Source
AI summary
Systems and methods for fleet inspection and maintenance using a robot are provided. The robot may detect a maintenance issue of a vehicle of a fleet of vehicles via one or more sensors, generate a navigation route to a position proximal to the maintenance issue of the vehicle, traverse along the navigation route to the position, and execute a maintenance to rectify the maintenance issue of the vehicle. The robot may include a mobile base removably coupled to a modular platform for performing a maintenance task.


