## 4 Conclusions  
The algorithm and implementation proposed in this paper have proven to fit their intended use in the subCULTron heterogeneous robotic swarm quite well, enabling surface platforms to dock smaller floating sensor nodes using a visual servoing approach, successfully starting wireless energy transfer in a variety of testing conditions with very simple changes in parameter tuning. In the future, these changes will be done autonomously, based on the environmental data measured by the vehicles themselves. Figure 24: aMussel image offsets during the docking experiment in the field. Triangular markers denote where each separate docking attempt ended. Figure 25: Two examples of image processing on the aPad during docking experiments in a realistic environment. From left to right: original image, hue thresholding output, neural network detection output. Note the neural network output being a frame behind the hue thresholding. Further work will include stress-testing of the wireless charging itself, as well as thorough testing and benchmarking of its efficiency. Although the mechanical design of the aPad docks and the aMussel top caps have so far shown to ensure satisfactory alignment and proximity of the transmitter and receiver coils, full testing of the long-term energy transfer efficiency and reliability remains to be done. The developed system has been used to charge aMussels during field trials; however, this was only done in strictly controlled conditions on land. As an additional aspect of long-term marine operations, the effects of biofouling on the operation of the swarm will be investigated. The docking system described here was briefly used in the validation of the exploration paradigm described and tested in [3], and it will be combined with both exploration and high-level decision-making and scheduling algorithms described in [27] in order to enable the examination of the cumulative effects of energy transfer systems on the longevity of the subCULTron swarm as a whole, in the interest of maximizing it and ensuring satisfactory, truly autonomous long-term environmental monitoring. Conceptualization, A.B., F.M. and N.M.; Methodology, A.B., F.M. and N.M.; Software, A.B. and F.M. ; Validation, A.B. and F.M. ; Formal analysis, A.B. and F.M. ; Writing--original draft preparation, A.B. ; writing--review and editing, A.B., F.M. and N.M.; Supervision, N.M. All authors have read and agreed to the published version of the manuscript. This work was supported in part by the Croatian Science Foundation under Project IP-2016-06-2082 \"Cooperative robotics in marine monitoring and exploration\", and in part by the European Union through the ERDF project KK.01.1.1.01.0009 \"DATACROSS--Advanced methods and technologies in Data Science and Cooperative Systems\", the H2020-EU.1.4.1.2. project \"EUMarineRobots\", and the H2020 FET-Proactive project \"subCULTron\", No. 640967. The work of [PERSON] was supported in part by the \"Young researchers' career development project--training of doctoral students\" of the Croatian Science Foundation funded by the European Union from the European Social Fund. The authors wish to thank the members of the consortium of the project'subCULTron' consisting of Artificial Life Lab--University of Graz, Unit of Social Ecology--Universite Libre de Bruxelles, Cybertronica Research, IRCCyN--Ecole des Mines de Nantes, BioRobotics Institute--Scuola Superiore Sant'Anna, CORILA: Consortium for coordination of research activities concerning the Venice lagoon system and ISMAR Istituto di Scienze Marine. The authors declare no conflict of interest.