Assisted painting of 3D structures using shared control with a hand-held robot

We present a shared control method of painting 3D geometries, using a handheld robot which has a single autonomously controlled degree of freedom. The user scans the robot near to the desired painting location, the single movement axis moves the spray head to achieve the required paint distribution. A simultaneous simulation of the spraying procedure is performed, giving an open loop approximation of the current state of the painting. An online prediction of the best path for the spray nozzle actuation is calculated in a receding horizon fashion. This is calculated by producing a map of the paint required in the 2D space defined by nozzle position on the gantry and the time into the future. A directed graph then extracts its edge weights from this paint density map and Dijkstra's algorithm is then used to find the candidate for the most effective path. Due to the heavy parallelisation of this approach and the majority of the calculations taking place on a GPU we can run the prediction loop in 32.6ms for a prediction horizon of 1 second, this approach is computationally efficient, outperforming a greedy algorithm. The path chosen by the proposed method on average chooses a path in the top 15% of all paths as calculated by exhaustive testing. This approach enables development of real time path planning for assisted spray painting onto complicated 3D geometries. This method could be applied to applications such as assistive painting for people with disabilities, or accurate placement of liquid when large scale positioning of the head is too expensive.