Dynamic Vehicle Servicing Paths for Safe Robotic Cleaning
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Solution Overview
Problem
Current automated guided vehicle servicing systems, such as robotic car washes, suffer from inefficiencies including extended wait times, damage to vehicles due to inflexible programming, mechanical wear, and safety issues like collisions and improper cleaning.
Innovation Solution
A system utilizing a constellation of sensors and computer vision devices to create a control framework for robotic vehicle servicing, enabling dynamic path planning and collision avoidance, with features like thermal imaging and machine learning to adapt to vehicle contours and ensure safe, efficient cleaning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a methodical step-by-step cleaning process is followed, then cleaning thoroughness is improved, but wait time increases
Solution Approach 1:
The system dynamically adjusts the cleaning path and process based on real-time sensor feedback about vehicle contours, dirt distribution, and sensitive areas. Rather than following a fixed step-by-step routine, the robotic system adapts its cleaning sequence and pressure application dynamically, allowing it to maintain thoroughness while reducing unnecessary movements and wait times.
Solution Approach 2:
The system changes cleaning parameters (pressure, speed, tool position) based on detected dirt scores and vehicle features. High-pressure water jets are applied selectively to heavily soiled areas identified by image capture devices, while sensitive areas receive reduced pressure or alternative cleaning methods, optimizing both thoroughness and efficiency.
2Device complexity
If fixed algorithms and pre-set routines are used, then system simplicity is improved, but adaptability to unique vehicle contours deteriorates
Solution Approach 1:
The robotic system performs self-calibration and self-adjustment based on sensor feedback. Image capture devices scan each vehicle's unique contours, and the system automatically generates an optimized cleaning path without requiring manual programming for each vehicle type. The system serves itself by adapting to whatever vehicle is presented, eliminating the need for complex pre-programming of numerous vehicle configurations.
Solution Approach 2:
The system continuously receives feedback from sensors, thermal imaging devices, and image capture devices during operation. This real-time feedback allows the control system to adjust the cleaning path, pressure, and tool positioning to match the actual vehicle contours and dirt distribution, achieving high adaptability while maintaining relatively simple fixed algorithms for path generation.
3Productivity
If high-pressure water jets and rotating brushes are used, then cleaning effectiveness is improved, but risk of vehicle damage increases
Solution Approach 1:
The system applies different cleaning intensities to different areas of the vehicle based on detected dirt scores and identified sensitive features. High-pressure jets and rotating brushes are concentrated on heavily soiled areas, while sensitive areas such as antennas, mirrors, and trim pieces receive reduced pressure or alternative gentle cleaning methods. This localized approach maintains overall cleaning effectiveness while minimizing damage risk to specific vulnerable areas.
Solution Approach 2:
The system performs preliminary scanning with image capture devices and thermal imaging to identify sensitive areas and potential damage risks before the cleaning process begins. The control system pre-plans the cleaning path to avoid or carefully navigate around identified vulnerable features, preventing damage before it can occur rather than relying solely on reactive measures during cleaning.
4Productivity
If robotic systems operate at high speed, then throughput is improved, but safety risks and collision probability increase
Solution Approach 1:
The system maintains continuous monitoring of the environment through sensors and thermal imaging devices throughout the cleaning process. This continuous feedback allows the robotic system to operate at high speeds while immediately detecting and responding to safety concerns such as unexpected obstacles, personnel entry, or vehicle movement, thereby maintaining both high throughput and safety through uninterrupted surveillance and adaptive path adjustment.
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 provides faster, safer, and more reliable vehicle servicing by dynamically adapting to vehicle features, minimizing damage, and ensuring operator safety, thereby enhancing customer satisfaction and operational efficiency.
Implementation Method 1
a service area is scanned with at least one thermal imaging device to determine if a person is within an area of interest
Implementation Method 2
a service area may be scanned with at least one image capture device to generate a dirt score that identifies at least one serviceable portion of the vehicle
Data Source
AI summary
A system for dynamically guided vehicle servicing may include scanning a service area with at least one image capture device to generate a dirt score that identifies at least one serviceable portion of the vehicle. In addition, the system may include generating a path along which end of arm tooling (EOAT) travels to perform a servicing operation on the at least one serviceable portion of the vehicle. The system may include moving the EOAT along the path in accordance with the dirt score and the servicing operation. Moreover, the device may include executing a damage mitigation operation if an unwanted overlap between a fenceless cell field of view and a service area field of view is detected.