This paper proposes a novel proportional-integral-derivative (PID) control approach that enables variable ballast systems on an autonomous underwater vehicle (AUV) to complement the underwater vehicle's hydroplanes when altitude-keeping over a variable seabed. This control approach is tested on an AUV computer simulator that features a variable ballast system model, which includes the capacity for free flow of seawater into and out of the ballast tank. The new control approach uses hydroplane deflection angle feedback as inputs to the variable ballast system controller in combination with a lowpass filter to ensure that the variable ballast system does not react to high hydroplane deflection rates and unnecessarily deplete the underwater vehicle's onboard energy supply. For the conditions modeled in this research, the resulting simulation case studies showed that this control approach enables the variable ballast system to effectively return control authority back to the hydroplanes while altitude-keeping to a variable seabed.
1 January 2020 in Proceedings of Meetings on Acoustics
The underwater acoustic channel is a difficult communication medium due to its variable link quality which depends on location, time and the environment. This paper reports on underwater channel characterization for shallow water (< 100 m) in the Atlantic offshore of Halifax, Canada. The underwater channel characteristics drives the level of multi-domain robot collaboration possible to characterize a floating target both above- and below-water. RF communications is used between the topside unmanned surface vehicle and unmanned aerial vehicle. Underwater, acoustic modems are used between the submerged part of the unmanned surface vehicle and the unmanned underwater vehicles. The outcome is a multi-domain picture of the floating target from the sensors on these collaborating robots. Before deployment, simulations were performed with a tool that integrates BELLHOP and newly developed complementary analysis capabilities in a MATLAB framework to determine operational ranges from range-dependent attenuation. The main contributions are an underwater acoustic environment-informed approach to placing mobile communicating nodes in a network, the network’s range predictions, channel analysis and a user-friendly GUI to manage the BELLHOP inputs and outputs. The approach and tools are validated in simulations and verified in-water. Transmission losses (TL) and underwater channel characteristics for illustrative cases are presented.
1 January 2021 in Proceedings of Meetings on Acoustics
Proposed, is a novel OFDM/CDMA communications network that runs on full-duplex software-defined underwater acoustic modems. This system is designed to detect, localize and track mobile underwater targets using multiple collaborating unmanned underwater vehicles (UUVs). This underwater network will be presented and described as a communications system. To start, the underwater channel characteristics (shallow, multi-path and high ambient) are described. The requirement is signal propagation that is secure (encoded), spread spectrum, robust to frequency selective fading, and efficient. This requirement is not easily met by existing full-duplex communications stacks. The proposed OFDM and CDMA modulation schemes better address this on embedded systems like UUVs. Therefore, the modem’s functions are integrated into the UUV with the Robot Operating System (ROS) middleware. These acoustic modems natively run UnetStack – a stack that focuses on underwater communication networks. The ROS nodes that control the UUV communicate to/with the modem using the UnetPy’s socket API. Scenarios are demonstrated where one stationary UUV/modem and two underway ones communicate in a full-duplex configuration. In the process, messages / signals on UUV/modem location, speed, heading, etc. are securely and efficiently exchanged among UUVs/modems. Finally, the proposed system is validated through UnetStack’s hardware-in-the-loop simulations (UnetSim) and multiple in-water tank trials.
19 September 2022 in Journal of Intelligent & Robotic Systems