Abstract
Maintenance of ship hull involves routine tasks during dry-docking that includes inspection, paint stripping, and re-painting. Among those, paint stripping is always seen as harmful for human operators and a time-consuming task. To reduce human risk, cost, and environmental cleanliness, the shipping maintenance industries started using robotic solutions. However, most of such robotic systems cannot operate fully autonomous since it requires human in the loop to monitor the cleaning efficiency. To this end, a novel autonomous self-evaluating hull cleaning robot called Hornbill is presented in this paper. The proposed robot is capable of navigating autonomously on the hull surface and perform water jet blasting to strip off the paint coating. The robot is also enabled with a Deep Convolutional Neural Network (DCNN) based self-evaluating scheme that benchmarks cleaning efficiency. We evaluated the proposed robot's performance by conducting experimental trials on a metal plate under three different paint coatings. While performing the paint stripping task in every experimental trial, the self-evaluating scheme would generate the heat map that depicts the plate's cleanliness. The results indicate that the proposed self-evaluating system could successfully generate high accurate cleanliness heat maps in all considered scenarios, which simplifies the checkup process for paint inspectors.
Highlights
Maintaining a smooth and foul free operation of ships involves a series of routine repair tasks
Such an effort increases the number of robotic products that are being used for ship hull maintenance task, and it is expecting to grow at a Compound annual growth rate (CAGR) of 16.2 between the year 2018 to 2027 [5]
We introduced the mechanical design, system architecture, and the autonomy navigation of the hornbill robot along with the Deep Convolutional Neural Network (DCNN) image classifier module
Summary
Maintaining a smooth and foul free operation of ships involves a series of routine repair tasks. Prabakaran Veerajagadheswar et al.: Hornbill: A Self-evaluating Hydro-blasting Reconfigurable Robot for Ship Hull Maintenance of mechanism design, autonomy, human-robot, and multirobot operation. The proposed robotic system can adapt to navigate on any curved surfaces in a ship hull In another similar work, Wei Song et al proposed a water blasting based hull cleaning robot with a permanent magnet adhesion system [14]. The proposed system can perform a water blast to strip existing paint in a ship hull at a low cost Most of these platforms were operated manually using a remote control without any autonomous capability and always had human in the loop. A viable approach to overcome this bottleneck in deploying an un-supervised hull paint stripping robot is to implement an advanced autonomous capability that can self-evaluate the cleaning performance.
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