Probabilistic localisation in repetitive environments: Estimating a robot's position in an aviary poultry house

One of the problems in loose housing systems for laying hens is the laying of eggs on the floor, which need to be collected manually. In previous work, PoultryBot was presented to assist in this and other tasks. Here, probabilistic localisation with a particle filter is evaluated for use inside poultry houses. A poultry house is a challenging environment, because it is dense, with narrow static objects and many moving animals. Several methods and options were implemented and tested on data obtained with PoultryBot in a commercial poultry house. Although no animals were present, the localisation problem is still challenging here because of the repetitive nature of the poultry house interior, with its many narrow obstacles. Different parameter configurations were systematically evaluated, based on accuracy and applicability of the results. Estimated paths were quantitatively evaluated based on the Euclidian distance to a ground-truth determined with help of a total station. The presented system reached an accuracy of 0.37 m for 95% of the time, with a mean error of 0.2 m, making it suitable for localising PoultryBot in its future application.