Path planning for the autonomous collection of eggs on floors

A problem in loose housing systems for laying hens is the laying of eggs on the floor; these eggs need manual collection. This job is heavy and time-consuming and automated collection is desired. For collection using a robot, a collection path is required. A novel path planning algorithm is introduced for non-uniform repetitive area coverage (NURAC) paths and evaluated based on information about floor egg distribution probability. Firstly, a spatial map was developed that describes the potential for floor eggs at each location in a poultry house. Next, paths for floor egg collection are planned with a dynamic programming approach that covers the house floor area and frequently revisits locations with a high potential on floor eggs. These paths are compared with the paths used for floor egg collection by a farmer and evaluated with help of a simulated set of floor eggs. With respect to the average time eggs are present on the floor, paths planned for a robot are compared to two collection rounds of a farmer. With respect to the structure of the path and the number of visits to locations with a high potential, the robot paths outperform the farmer. Although optimality of the path is not guaranteed, the presented results are promising for the use of a robot to collect floor eggs, and will result in a reduction of the demand for manual labour. Extending the floor egg model with feedback information could further improve the results. •Path planner for non-uniform repetitive coverage of areas, e.g. floor egg collection.•Performance of planned paths was compared with collection of floor eggs by a farmer.•Robot paths led to more visits to specific areas where more eggs are expected.•Time eggs spent at the floor during robot collection was similar to farmer collection.•Results favour the use of robots to collect floor eggs which reduce human labour.