## 3 Results and Discussion
### Challenging Environment Test  
The realistic environment docking experiment took place during a prolonged set of field trials for the subCULTron project in July 2019, on a particularly windy day with rough, choppy waves making for challenging conditions but providing a good opportunity to test the operational limits of the docking system (see Figure 21). The subCULTron robots were deployed off a pontoon, with a designated open sea workspace next to a relatively low-traffic water route (Figure 22). Unlike the structured experiment, no data about the aMussel's position was available. Image-derived data and information about when each of the docking attempts started and concluded were collected. Figure 21: Wind speed and direction during the 2019 field trials, as collected by the Malamocco weather station. The docking experiment taking place during 4 July is shown in red. Note all other wind peaks occurred during night, with a storm taking place the evening of 3 July. Figure 20: Offsets during the docking experiment. Five separate successful docking attempt completions marked in red. Figure 23 presents the full trajectory of the aPad during the experiment, with color-coded segments showing when each of the mission primitives were active and markers showing the moment of each docking and undocking. The aMussel was drifting in currents of varying strengths towards the northwest of the given image, leading to noticeable differences in position between where the aPad leaves it after undocking and where it is later caught (i.e., the black markers on the trajectory plot). A video including visual feeds from the Kinect, image processing and EKF data, and a mission replay constructed from the aPad mission data logs for the autonomous docking field experiment can be seen at [[https://www.youtube.com/watch?v=Agky3](https://www.youtube.com/watch?v=Agky3) vv6 Mh4]([https://www.youtube.com/watch?v=Agky3](https://www.youtube.com/watch?v=Agky3) vv6 Mh4). Figure 24 gives a full timeline of the image offsets detected by the hue thresholding and the neural network, as well as the final filter output for the sequence of six successful docking and undocking attempts. Both docking attempts and undockings can be clearly seen, as the offsets reflect how the aPad approaches the target and captures it, then, after holding it for a while, releases it and moves away. This corresponds to the previously discussed results shown in Figure 16. Please note that the filter node was only running during docking attempts, so there are no filter output data points between the conclusion of each attempt and the start of the next one. Figure 23: Full mission trajectory of the Venice docking experiment in challenging conditions. The aPad is represented by a black circular marker and its heading denoted by a red arrow. The X markers designate successful docking attempts, while the black diamond markers signify undockings. Figure 22: On-site experiments in the Venice lagoon. The pontoon off which robots were deployed (**top left**), field trials in progress (**top right**), mission supervision interface showing highlighted experiment area (**bottom**). As briefly noted in Section 2.2, experiments in real conditions in the lagoon led to a tuned increase in all regulator parameters, as the ones previously used made for an aMussel-catching approach that, while successful, was very slow and tentative in the presence of waves and wind and sea currents. To accommodate the aMussel bobbing up and down on the waves and briefly being lost from the aPad's view, the parameter for the tracking filter heuristic that ensures continuous measurements and rejects fleeting outlier detections was set to only require 3 consecutive frames of detection as opposed to the original 6. While here the switch was done manually, to accommodate the need for this level of adaptability, automated switching between \"modes\" depending on the output of the aPad's IMU will be implemented.