Robot assisted floor surface mapping and modelling for prediction of grind finish : submitted to the School of Engineering and Advanced Technology in partial fulfillment of the requirements for the degree of Master of Engineering, Mechatronics, at Massey University, Auckland

Abstract

Mapping and localisation is a fundamental aspect of mobile robotics as all robots must successfully know their surroundings and location for navigation and manipulation. For some navigation tasks, prior knowledge of the 3D environment, in particular the 3D surface profile, can greatly improve navigation and manipulation tasks such as contacting, sensor inspecting, terrain traversability, and modifications. This thesis presents the investigation into the capability of cheap and accessible sensors to capture the floor surface information and assesses the ability for the 3D representation of the floor to be used as prior knowledge for a model. A differential drive robotic platform was developed to perform testing and conduct the research. 2D localisation methods were extrapolated into 3D for the floor capturing process. The robotic system was able to successfully capture the floor surface profile of a number of different type floors such as carpet, asphalt, and a coated floor. Two different types of sensor, a 2D laser scanner and an RGB-D camera, were used for comparison of the floor capture ability. A basic model was developed to estimate the floor surface information. The captured surface was used as prior knowledge for the model, and testing was performed to validate the devised model. The model performed well in some areas of the floor, but requires further development to improve the performance. Further validation testing of the system is required, and the system can be improved by improvement of 3D localisation, minimisation of sensor errors, and further testing into the application.