Robotic Joint Compound Application With Vision-Guided Seam Detection
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Solution Overview
Problem
Construction tasks such as finishing walls with drywall panels and filling joints are labor-intensive and physically straining for workers, leading to potential injuries, and robots struggle to accurately locate and apply materials to targeted areas.
Innovation Solution
A robotic system with sensors, computer vision, and machine learning for seam detection, combined with a user interface for feedback, allows precise application and removal of materials using a robotic arm and end effector, guided by a planner that considers environmental conditions and constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual methods are used for wall finishing tasks, then workers can perform tasks with flexibility and judgment, but workers experience physical strain and potential injuries
Solution Approach 1:
The patent replaces manual mechanical operations with an automated robotic system that uses sensors, computer vision, and controlled material application mechanisms. The robotic arm with end effector automatically applies joint compound to seams, eliminating the need for workers to manually handle heavy tools and perform repetitive straining motions.
2Productivity
If robotic systems are used for material application, then productivity and safety are improved, but precision in locating and applying materials to targeted areas is reduced
Solution Approach 1:
The robotic system incorporates sensors and computer vision that continuously detect seam locations and provide feedback to the control system. This feedback loop enables the robot to accurately locate seams, adjust its positioning, and precisely apply joint compound to the targeted areas, maintaining high manufacturing precision while achieving full automation.
Solution Approach 2:
The patent introduces an intermediary layer of computer vision and sensor processing between the robotic actuation system and the material application process. This intermediary system translates visual detection of seams into precise robotic positioning and material deposition, bridging the gap between automation and precision.
3Productivity
If automated robotic systems are implemented, then labor intensity is reduced, but system complexity increases
Solution Approach 1:
The robotic system is designed as a multi-functional platform that integrates sensor detection, computer vision processing, seam identification, and material application capabilities within a single unified system. This universal approach consolidates multiple functions into one system rather than requiring separate devices for each task, managing complexity through integration.
Data Source
AI summary
The present disclosure describes systems and methods for detecting data corresponding to an object and selectively affect, based at least in part on the data, a material on the object. In some embodiments, the data is, at least in part, used to selectively apply a material to the object, selectively avoid applying a material to the object; selectively remove at least a portion of a material from the object; and/or selectively avoid removing at least a portion of a material from the object.