Adnan Abdullah

Adnan Abdullah, Alankrit Gupta, Vaishnav Ramesh et al.

Adaptive mission control and dynamic parameter reconfiguration are essential for autonomous underwater vehicles (AUVs) operating in GPS-denied, communication-limited marine environments. However, AUV platforms generally execute static, pre-programmed missions or rely on tethered connections and high-latency acoustic channels for mid-mission updates, significantly limiting their adaptability and responsiveness. In this paper, we introduce NemeSys, a novel AUV system designed to support real-time mission reconfiguration through compact magnetoelectric (ME) signaling. We present the full system design, control architecture, and a mission encoding framework that enables interactive exploration and task adaptation via low-bandwidth communication. The proposed system is validated through analytical modeling, controlled simulation tests, and real-world trials. The mid-mission retasking scenarios, evaluated using the NemeSys digital twin, demonstrate behavior switching latency below 50 ms with only a 13.2 MB peak computational overhead, making the framework suitable for deployment on edge computing hardware. Laboratory tank tests and open-water field trials further confirm stable control and reliable mission execution in dynamic underwater environments. These results establish the feasibility of online mission reconfiguration and highlight NemeSys as a promising step toward responsive, goal-driven adaptive underwater autonomy.

Adnan Abdullah, Ruo Chen, Ioannis Rekleitis et al.

Underwater ROVs (Remotely Operated Vehicles) are indispensable for subsea exploration and task execution, yet typical teleoperation engines based on egocentric (first-person) video feeds restrict human operators' field-of-view and limit precise maneuvering in complex, unstructured underwater environments. To address this, we first propose EgoExo, a geometry-driven solution integrated into a visual SLAM pipeline that synthesizes on-demand exocentric (third-person) views from egocentric camera feeds. We further propose EgoExo++, which extends beyond 2D exocentric view synthesis (EgoExo) to augment a piecewise planar 2.5D ground surface estimation on-the-fly. Its anchor-free aerial viewpoint supports ground-relative reasoning, such as clearance and terrain-based navigation marker following. The computations involved are closed-form and rely solely on egocentric views and monocular SLAM estimates, which makes it portable across existing teleoperation engines and robust to varying waterbody characteristics. We validate the geometric accuracy of our approach through extensive experiments of 2-DOF indoor navigation and 6-DOF underwater cave exploration in challenging low-light conditions. To assess operational benefits, we conduct two user studies with simulation and real-world data, each involving 15 participants, comparing baseline egocentric teleoperation and EgoExo++. Results indicate improved system usability (SUS), reduced perceived workload (NASA-TLX), and significant gains in objective teleoperation performance, including 16% faster missions, 5-fold reduction in path deviation ratio, and fewer collision events (2 vs. 5 across trials). Furthermore, we highlight the role of EgoExo++ augmented visuals in supporting shared autonomy and embodied teleoperation. This new interactive approach to ROV teleoperation presents promising opportunities for future research in subsea telerobotics.