In this project we aim to demonstrate an adaptive paint stripping robot with efficient path planning. Robotized solutions to remove paint are developed in the past two centuries and prove to be competitive on large projects compared to human labor. In order to reduce the allocation of people in hazardous environments we aim to validate a next generation paint stripping robot, which is more efficient and effective. Asset owners are demanding automation of the paint removal process but are very aware of the costs. Due to this, they still choose for human labor in smaller projects. Surrotec was able to establish a business model for robotized maintenance, doing 50 projects yearly (storage tanks and ship hulls). We aim to reduce the overlapping paths from 33% to 5% and measure the rawness of the surface in order to adapt speed of the operation. By this, we can save time, money and reduce emissions.