This paper describes the open-source software toolchain developed by the Underwater Systems and Technology Laboratory (LSTS) for supporting networked heterogeneous air and ocean vehicle systems. The toolchain supports the deployment of air and ocean vehicles interacting over limited acoustic and wireless networks combined with disruption-tolerant networking protocols. We present the different components of the toolchain and how they can be deployed and extended for different scenarios. We conclude with descriptions of recent applications to onboard deliberative planning and integration of low-cost micro UAVs into the toolchain.

This study describes rapid prototype construction of small and lightweight push broom Hyper Spectral Imagers (HSI). The dispersive element housings are printed by a thermoplastic 3D printer combined with S-mount optical components and commercial off-the-shelf camera heads. Four models with a mass less than 200 g are presented with a spectral range in the visible to the near-infrared part of the electromagnetic spectrum. The bandpass is in the range from 1.4 - 5 nm. Three test experiments with motorized gimbals to stabilize attitude show that the instruments are capable of push broom spectral imaging from various platforms, including airborne drone to handheld operations.

Obtaining synoptic observations of dynamic ocean phenomena such as fronts, eddies, oxygen minimum zones and blooms has been challenging primarily due to the large spatial scales involved. Traditional methods of observation with manned ships are expensive and, unless the vessel can survey at high-speed, unrealistic. Autonomous underwater vehicles (AUVs) are robotic platforms that have been making steady gains in sampling capabilities and impacting oceanographic observations especially in coastal areas. However, their reach is still limited by operating constraints related to their energy sources. Unmanned aerial vehicles (UAVs) recently introduced in coastal and polar oceanographic experiments have added to the mix in observation strategy and methods. They offer a tantalizing opportunity to bridge such scales in operational oceanography by coordinating with AUVs in the water-column to get in-situ measurements. In this paper, we articulate the principal challenges in operating UAVs with AUVs making synoptic observations for such targeted water-column sampling. We do so in the context of autonomous control and operation for networked robotics and describe novel experiments while articulating the key challenges and lessons learned.

Over the last decade, ocean sunfish movements have been monitored worldwide using various satellite tracking methods. This study reports the near-real time monitoring of fine-scale (< 10 m) behaviour of sunfish. The study was conducted in southern Portugal in May 2014 and involved satellite tags and underwater and surface robotic vehicles to measure both the movements and the contextual environment of the fish. A total of four individuals were tracked using custom-made GPS satellite tags providing geolocation estimates of fine-scale resolution. These accurate positions further informed sunfish areas of restricted search (ARS), which were directly correlated to steep thermal frontal zones. Simultaneously, and for two different occasions, an Autonomous Underwater Vehicle (AUV) video-recorded the path of the tracked fish and detected buoyant particles in the water column. Importantly, the densities of these particles were also directly correlated to steep thermal gradients. Thus, both sunfish foraging behaviour (ARS) and possibly prey densities, were found to be influenced by analogous environmental conditions. In addition, the dynamic structure of the water transited by the tracked individuals was described by a Lagrangian modelling approach. The model informed the distribution of zooplankton in the region, both horizontally and in the water column, and the resultant simulated densities positively correlated with sunfish ARS behaviour estimator (r_s = 0.184, p<0.001). The model also revealed that tracked fish opportunistically displace with respect to subsurface current flow. Thus, we show how physical forcing and current structure provide a rationale for a predator’s fine-scale behaviour observed over a two weeks in May 2014.