Towards Proactive Decentralized Adaptation of Unmanned Aerial Vehicles for Wildfire TrackingSHORT
Smart Cyber-Physical Systems (sCPS) operate in dynamic and uncertain environments, where anticipation to adverse situations through effective decision-making is crucial and decentralization is often necessary due to scalability, resilience, and effiency reasons. Addressing the limitations related to the lack of foresight of (decentralized) reactive self-adaptation (e.g., slower response, sub-optimal resource usage), this paper introduces a novel method that employs Predictive Coordinate Descent (PCD) to enable decentralized proactive self-adaptation in sCPS. Our study compares our proactive PCD approach with a reactive Deep Q-Network (DQN)-based strategy on Unmanned Aerial Vehicles (UAVs) in wildfire tracking adapta- tion scenarios. Results demonstrate the effectiveness of PCD, which outperforms DQN both under standard operational conditions, as well as in challenging scenarios with limited observability of the environment.
Mon 15 AprDisplayed time zone: Lisbon change
14:00 - 15:30 | Session 3: Unmanned Aerial Vehicles and LLMs Research Track / Artifact Track at Luis de Freitas Branco Chair(s): Gabriel A. Moreno Carnegie Mellon University Software Engineering Institute | ||
14:00 25mTalk | ADAM: Adaptive Monitoring of Runtime Anomalies in Small Uncrewed Aerial SystemsFULL Research Track Md Nafee Al Islam University of Notre Dame, Jane Cleland-Huang University of Notre Dame, Michael Vierhauser University of Innsbruck | ||
14:25 15mTalk | Towards Proactive Decentralized Adaptation of Unmanned Aerial Vehicles for Wildfire TrackingSHORT Research Track Enrique Vilchez University of Malaga, Javier Troya Universidad de Málaga, Spain, Javier Camara University of Málaga | ||
14:40 15mTalk | Wildfire-UAVSim: An Exemplar for Evaluation of Adaptive Cyber-Physical Systems in Partially-Observable EnvironmentsARTIFACT Artifact Track Enrique Vilchez University of Malaga, Javier Troya Universidad de Málaga, Spain, Javier Camara University of Málaga | ||
14:55 15mTalk | Aloft: Self-Adaptive Drone Controller TestbedARTIFACT Artifact Track Calum Imrie University of York, Rhys Howard University of Oxford, Divya Thuremella University of Oxford, Nawshin Mannan Proma University of York, Tejas Pandey University of York, Paulina Lewinska University of York, Ricardo Cannizzaro University of Oxford, Richard Hawkins University of York, Colin Paterson University of York, Lars Kunze University of Oxford, Victoria J. Hodge University of York | ||
15:10 15mTalk | Exploring the Potential of Large Language Models in Self-adaptive SystemsSHORT Research Track Jialong Li Waseda University, Japan, Mingyue Zhang Southwest University, NIANYU LI ZGC Lab, China, Danny Weyns KU Leuven, Zhi Jin Peking University, Kenji Tei Tokyo Institute of Technology | ||