# Design and Implementation of an Autonomous Charging Station for Agricultural Electrical Vehicles
## 1 Introduction  
Energy industries, manufacturing industries, traffic and the transport sector contribute significantly to greenhouse gas (GHG) emissions, and so does agriculture. Nevertheless, there is a major area that may be considered as \"low-hanging fruit\" in terms of GHG mitigation, which is the reduction of the emissions from agriculture, mainly tractor-related activities on the farm. To this end, several efforts are conducted from large tractor manufacturers [1, 2] to provide an electrical alternative to the conventional fossil-based tractors. However, we believe that the main reason for the lack of commercially available electrical tractors, especially when compared to the growing success of electrical vehicles (EVs), is related to the strategy that these tractor manufacturers are following, namely when trying to provide the electrical alternatives with the same characteristics as the fossil-based ones. Because batteries have poorer mass energy density than fossil fuels, an electric tractor must be significantly heavier than a similarly powered diesel tractor in order to achieve a similar run-time. This will thus increase problems related to soil compaction, and raise concerns about the balance between charging versus working time [3]. Nevertheless, an alternative option is to replace heavy fossil-based tractors with a fleet of smaller, lighter tractors [4], or more recently a fleet of robots [5] that can work in a cooperative manner. The focus on greener alternatives of fossil-based machinery is on the rise [6], as the need for more sustainable practices to reduce the GHG emissions from the agricultural sector is considered in many countries as priority. In addition to that,the advantages of shifting to electrical alternatives of conventional agricultural machinery are numerous, as the electrical equivalent requires less maintenance [3], while there is a huge potential in producing the energy required directly on the farm [7]. In contrast, some challenges are to be solved before making this green shift a viable solution to the farmers, especially on the logistics side, as a fleet of small electrical tractors/robots will need to recharge their batteries more often as the battery packs size on these vehicles are small, and the current battery technology allows at best around 5 h of continuous labor for a 30 kW (40 horse power HP diesel-equivalent) commercially available electrical tractor [8], or for up to ten hours for an electrical weeding robot [9]. This means that if in a scenario where a farmer is in possession of a fleet of small size agricultural electrical vehicles (AEVs) that operate autonomously around the clock in a cooperative manner [10], there will be a need to manage the recharging process of their batteries, without this becoming an additional burden, otherwise it leads to an increased demand for manpower, which is already problematic in the agricultural sector [11]. To solve this problem, one can think about a similar solution to home vacuum cleaning robots, or industrial mobile platforms, where the mobile platforms docks into a specially fitted docking mechanism to recharge the batteries. To reach this, usually vision [12] is used in order to define the placing of the docking station, as this is usually the easiest thanks to the large body of existing computer vision software and hardware. In addition to that, it is considered to be the most-used method to define the position of the docking area when taking a fixed landmark as a reference [13]. Other efforts to use different sensing methods to define the position of the docking station were carried out, such as infrared (IR) [14], laser-based techniques [15], or even radio frequency identifiers (RFID) [16]. Regardless of the sensing method used to identify the docking area, each proposed solution is a customized one, fitted to a dedicated platform.