Add RAS paper wind turbine. Update CV.

_bibliography/refs.bib

@@ -4,10 +4,10 @@ @ARTICLE{Silano2024IEEECommMagazine
  group        = {journals},
  preprint     = {publications/IEEEComMag_2024.pdf},
  doi          = {10.1109/MCOM.001.2400421},
+ link         = {https://ieeexplore.ieee.org/document/10829762},
  journal      = {IEEE Communications Magazine},
- year         = {2024},
+ year         = {2025},
  status       = {In Press},
- link         = {},
  month        = {},
  pages        = {},
  volume       = {},
@@ -30,22 +30,21 @@ @INPROCEEDINGS{Silano2024IROS_WS_CONTRIBUTION_FORMAL_METHODS
   abstract     = {This paper presents a method for task allocation and trajectory generation in cooperative inspection missions using a fleet of multirotor drones, with a focus on wind turbine inspection. The approach generates safe, feasible flight paths that adhere to time-sensitive constraints and vehicle limitations by formulating an optimization problem based on Signal Temporal Logic (STL) specifications. An event-triggered replanning mechanism addresses unexpected events and delays, while a generalized robustness scoring method incorporates user preferences and minimizes task conflicts. The approach is validated through simulations in MATLAB and Gazebo, as well as field experiments in a mock-up scenario.}
 }
 
-@INPROCEEDINGS{Silano2024RAS,
+@ARTICLE{Silano2024RAS,
  author       = {{Silano}, Giuseppe and {Cabellero}, Alvaro and {Liuzza}, Davide and {Iannelli}, Luigi and {Bogdan}, Stjepan and {Saska}, Martin},
  title        = {{A Signal Temporal Logic Approach for Task-Based Coordination of Multi-Aerial Systems: a Wind Turbine Inspection Case Study}},
  year         = {2025},
  group        = {journals},
  status       = {In Press},
  journal      = {Robotics and Autonomous Systems},
- link         = {},
  month        = {},
  pages        = {},
  volume       = {},
  number       = {},
  pages        = {1-16},
  preprint     = {publications/2409.12713v1.pdf},
- link         = {https://arxiv.org/abs/2409.12713},
- doi          = {10.48550/arXiv.2409.12713},
+ link         = {https://www.sciencedirect.com/science/article/pii/S0921889024002896},
+ doi          = {10.1016/j.robot.2024.104905},
  abstract     = {The paper addresses task assignment and trajectory generation for collaborative inspection missions using a fleet of multi-rotors, focusing on the wind turbine inspection scenario. The proposed solution enables safe and feasible trajectories while accommodating heterogeneous time-bound constraints and vehicle physical limits. An optimization problem is formulated to meet mission objectives and temporal requirements encoded as Signal Temporal Logic (STL) specifications. Additionally, an event-triggered replanner is introduced to address unforeseen events and compensate for lost time. Furthermore, a generalized robustness scoring method is employed to reflect user preferences and mitigate task conflicts. The effectiveness of the proposed approach is demonstrated through MATLAB and Gazebo simulations, as well as field multi-robot experiments in a mock-up scenario.}
 }