1 Department of Electronic Systems, The Technical Faculty of IT and Design, Aalborg University, VBN2 Aalborg U Robotics, The Faculty of Humanities, Aalborg University, VBN3 Automation & Control, The Technical Faculty of IT and Design, Aalborg University, VBN4 The Faculty of Engineering and Science (TECH), Aalborg University, VBN5 Aarhus University, Department of Engineering, Blichers Allé 20, 8830 Tjele, Denmark6 University of Turin, Faculty of Agriculture, DEIAFA Department Via Leonardo da Vinci 44, 10095, Grugliasco, Turin, Italy
Harvesting and mowing operations are among the main potential stressors affecting wildlife within agricultural landscapes, leading to large animal losses. A number of studies have been conducted on harvesting practices to address the problem of wildlife mortality, providing a number of management actions or field area coverage strategies. Nevertheless, these are general rules limited to simple-shaped fields, and which are not applicable to more complex operational situations. The objectives of the present study were to design a system capable of deriving a wildlife avoidance driving pattern for any field shape complexity and field boundary conditions (in terms of escape and non-escape areas) and applicable to different animal behaviours. The assumed animal escape reactions are the result of the parameterization of a series of developed behavioural functions. This parameterization will be able to adapt any knowledge that is or might become available as a result of dedicated future experiments on animal behaviour for different species or different animal ages.
International Journal of Advanced Robotic Systems, 2014, Vol 11, Issue 1
operations management; field robotics; path planning; Field robotics; Operations management; Path planning