# Wireless Remote Control for Underwater Vehicles
## 6 Conclusions  
In this paper, we designed and evaluated a wireless remote control for underwater vehicles in light of the capabilities offered by current optical, RF, and acoustic modem technologies. For each technology, we focused on the available modems that report performance figures measured in the presence of realistic operational conditions, including turbidity, sunlight noise, channel geometry, and the noise cause by the vehicle's propellers. We then identified three operational modes based on the quality of service needed to pilot an HROV with incremental level of autonomy by defining all traffic types that each mode should be able to transmit through the underwater channel. Specifically, the vehicle can be piloted as an inspection-class ROV up to a range of few tens of meters, depending on the working conditions, while it can perform semiautonomous missions with a high control quality up to a range of few hundred of meters and quasi-autonomous missions up to a distance of 10 km. Actual samples of real streams have been used both to estimate the throughput that each mode needs to support and to generate the data packets transmitted in our simulation.  
We designed and implemented in the DESERT Underwater framework a multimodal communication layer able to support different QoS for each traffic type to be transmitted, with the use of dedicated queues that can also be used for traffic shaping by setting the minimum delay between subsequent packets of the same traffic type. Via simulations, we were able to tune this delay of not-time-stringent burst traffics in order to prioritize all traffics with real-time requirements. To this aim, we also inspect the effects caused by a de-jitter buffer able to limit packet delay variation at the cost of a higher delivery delay. We analyzed the root mean square error of the path followed by  
Figure 12: Transmitted and received instantaneous video bit rates of VHQC (**a**) and VHQG (**b**), calculated on a time window of 1 s.  
Figure 13: PDV and average delay of VHQC and VHQG when using different traffic shaping configurations (**a**) and PDV when the traffic shaping forces an image packet delay of 40 ms (**b**).  
the HROV compared to the desired path that resulted in always being less than 0.6% of the distance between the HROV and the control station. Nevertheless, the accuracy of the actual trajectory relative to the desired one can be improved by increasing the guard time between subsequent commands, at the price of a longer mission and, therefore, the need for a higher battery capacity.  
Future works will focus on realizing a proof-of-concept prototype (PoC) of the system and on evaluating it through a field test.  
Conceptualization, F.C. and A.S.; methodology, A.S. and F.C.; data curation, A.S.; investigation, F.C.; formal analysis, A.S.; software, A.S.; validation, F.C.; writing--original draft preparation, F.C.; supervision, M.Z.; resources, M.Z.; visualization, A.S. and F.C.; project administration, M.Z.; funding acquisition, M.Z. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The authors declare no conflict of interest.