Robotic Painting: Mimicking Human Applicators
Who is working on this project: Karan Bansal, Yayun Du, Eric Palan, Zhaoxing Deng, Zicheng Fang, Yunbo Wang, Taiki Nagata, Mohiuddin Quadir
Robotically assisted painting is widely used for spray and dip applications. However, use of robots for coating substrates using a roller applicator has not been systematically investigated. We showed for the first time, a generic robot arm-supported approach to painting engineering substrates using a roller with a constant force at an accurate joint step, while retaining compliance and thus safety.
We introduce a cost-effective method to employ a general purpose robot (Sawyer, Rethink Robotics) for autonomous coating. To sense the position and the shape of the target object to be coated, the robot is combined with an RGB-Depth camera. The combined system autonomously recognizes the number of faces of the object as well as their position and surface normal. Unlike related work based on two-dimensional RGB-based image processing, all the analyses and algorithms here employ three-dimensional point cloud data (PCD). The object model learned from the PCD is then autonomously analyzed to achieve optimal motion planning to avoid collision between the robot arm and the object. To achieve human-level performance in terms of the quality of coating using the bare minimum ingredients, a combination of our own passive and builtin active impedance control is implemented. The former is realized by installing an ultrasonic sensor at the end-effector of robot working with a customized compliant mass-spring-damper roller to keep a precise distance between the end-effector and surface to be coated, maintaining a fixed force. Altogether, the control approach mimics human painting as evidenced by experimental measurements on the thickness of the coating.
(a) Sawyer paints the planar surface with a compliant roller exploiting position feedback control. (b) End-effector (compliant roller) comprised of (1) roller cover, (2) spring-damper system, and (3) the circuit including the microcontroller (Adafruit Pro Trinket 5V) and an ultrasonic sensor.
We found that, robotically- and human painted panels showed similar trends in dry film thickness, coating hardness, flexibility, impact resistance, and microscopic properties. Color profile analysis of the coated panels showed non-significant difference in color scheme and is acceptable for architectural paints. Overall, this work shows the potential of robot-assisted coating strategy using roller applicator. This could be a viable option for hazardous area coating, high-altitude architectural paints, germs sanitization, and accelerated household applications.
This work was done in collaboration with North Dakota State University (Prof. Mohi Quadir).
Publication: Bansal, K., Du, Y., Palan, E., Quadir, M., Jawed, M.K, 2022 Robotic Painting: Mimicking Human Applicators. In press with Journal of Coatings Technology and Research. Du, Y., Deng, Z., Fang, Z., Wang, Y., Nagata, T., Bansal, K., Quadir, M., Jawed, M.K, 2020 Vision and Force Based Autonomous Coating with Rollers. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Funding: We acknowledge support from the National Science Foundation (NSF) under award number IIS-1925360.
GitHub: https://github.com/duyayun/Vision-and-force-control-automonous-painting-with-rollers