Semi-Automatic Painting Robot for Interior Walls
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Solution Overview
Problem
Conventional painting methods for interior walls, particularly around window frames, are time-consuming, costly, and often result in imperfect masking and finishing, with traditional masking techniques being cumbersome and inefficient.
Innovation Solution
A semi-automatic painting robot system that includes a user device with image capturing, affine transformation, and co-ordinate transformation modules, and a semi-automatic painting robot equipped with a spray gun, servo motors, and a microprocessor, allowing for precise navigation and painting strokes to avoid non-paintable areas and achieve uniform coverage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional brush painting and masking methods are used, then painters can manually control the painting process, but the process becomes time-consuming and the final appearance is frequently imperfect
Solution Approach 1:
The patent replaces manual brush painting with an automated spray gun system controlled by a robotic arm. The robotic arm with spray gun automatically applies paint to the wall surface based on pre-processed wall images, eliminating manual brush operations and significantly increasing painting speed while maintaining precision through automated control.
Solution Approach 2:
The system processes the wall image to automatically identify paintable and non-paintable areas, then autonomously navigates the robotic arm to apply paint only where needed. The system serves itself by making autonomous decisions about painting paths and areas without continuous human intervention, improving both speed and precision.
2Object-affected harmful factors
If masking tape is applied to protect window frames, then window areas can be protected from paint, but the masking process is time-consuming and tedious
Solution Approach 1:
The system extracts and identifies non-paintable areas (such as window frames) from the processed wall image through image processing algorithms. By digitally segmenting the wall image into paintable and non-paintable regions, the system eliminates the need for physical masking tape while still achieving complete protection of window areas from paint.
Solution Approach 2:
The patent replaces the mechanical masking process with digital image processing and automated robotic navigation. The system uses computer vision to identify and avoid non-paintable areas, substituting the manual application and removal of masking tape with automated digital recognition and avoidance, thereby eliminating masking time entirely.
3Manufacturing precision
If spray guns are used for painting, then uniform paint distribution can be achieved, but the complexity of the painting system increases
Solution Approach 1:
The robotic arm system serves multiple functions: it positions the spray gun, controls painting speed, adjusts spray direction, and navigates around obstacles. This multi-functional robotic platform achieves uniform paint distribution while consolidating multiple control functions into a single automated system, managing complexity through integration rather than increase.
Solution Approach 2:
The system processes wall images to create a digital map of the painting area, then uses this information to guide the robotic arm's movements and spray gun operations in real-time. This feedback loop ensures uniform paint application by continuously adjusting the robotic arm's position and spray parameters based on the pre-processed wall geometry and identified paintable areas.
4Adaptability or versatility
If manual brushing of trim is performed, then painters can work around window frames, but the process is costly and the final appearance is frequently imperfect
Solution Approach 1:
The patent replaces manual brush work with automated spray application controlled by a robotic arm. The robotic system processes the wall image to precisely identify trim and window frame locations, then automatically adjusts its painting path to apply paint uniformly up to the edges of non-paintable areas, achieving superior finish quality without manual intervention.
Solution Approach 2:
The system performs preliminary processing of the wall image to identify and map out non-paintable areas before the actual painting begins. This advance preparation allows the robotic arm to pre-calculate optimal painting paths that automatically adapt to the wall's features, ensuring perfect finish quality around trim and windows without requiring manual adjustment during painting.
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 significantly reduces painting time and improves the quality of the finish by enabling efficient and precise application of paint, minimizing manual intervention and ensuring superior paint coverage compared to traditional brush painting methods.
Implementation Method 1
spray guns have replaced paint rollers. Spray guns have long been used to effect uniform distribution of paint
Implementation Method 2
Spray guns have long been used to effect uniform distribution of paint
Implementation Method 3
a magnetometer, and a microprocessor. The microprocessor executes all functions in the semi-automatic painting robot
Implementation Method 4
The magnetic field sensor module is configured to measure magnetic field orientation readings of the semi-automatic painting robot with respect to earth's magnetic field
Data Source
AI summary
A system for painting an interior wall of housing is disclosed. The system includes a semi-automatic painting robot 106 and a user device 104. The semi-automatic painting robot 106 includes a microprocessor 304, a servo drive module 306, a DC motor drive module 316, a magnetometer 312, a distance sensor module 318, a first servo motor 708, a second servo motor 714, a spray gun 710, and a belt driven linear actuator 804. A user device 104 captures one or more images of the interior wall to be painted, processes and sends the one or more images to the microprocessor 304 in co-ordinates of the interior wall. The microprocessor 304 receives the co-ordinates and performs the operations of painting on the interior wall using one or more painting strokes. The user 102 may control the semi-automatic painting robot 106 with the user interface present in the user device 104.