As military, power, civil and commercial applications continue to develop, it is anticipated that the Unmanned Aerial/Ground Vehicle (UAGV) market grow dramatically by 2020. These advancements, along with increasing scientific interest in UAGVs, are motivating commercial interest in the unmanned market. This technology offers a unique range of features, high-risk mission acceptance and most remarkably ultra-long endurance, which cannot be reasonably achieved by manned aircraft. The interest and demand for UAVs is on the rise particularly for the purpose of saving lives because it can be coupled with advances in automation and sensor technologies and also it’s potential for cost savings. Although, UAGVs have wonderful features but privacy, automation, fault detection and security are main problems with UAGVs which raise a lot of concern in recent years. Furthermore, UAGVs under uncertainties and faults increased the concern of using them in autonomous mode. RANCS research group objective is to address these problems with using advance methods and techniques. There are three main applications that RANCS research focuses: Transportation and construction, power applications and natural disaster usage.
- Abbaspour, Alireza, Kang K. Yen, Parisa Forouzannezhad, and Arman Sargolzaei. “A Neural Adaptive Approach for Active Fault-Tolerant Control Design in UAV.” IEEE Transactions on Systems, Man, and Cybernetics: Systems 99 (2018).
- Aboutalebi, Payam, Alireza Abbaspour, Parisa Forouzannezhad, and Arman Sargolzaei. “A novel sensor fault detection in an unmanned quadrotor based on adaptive neural observer.” Journal of intelligent & robotic systems 90, no. 3-4 (2018): 473-484.
- Abbaspour, Alireza, Michael Sanchez, Arman Sargolzaei, Kang Yen, and Nalat Sornkhampan. “Adaptive Neural Network Based Fault Detection Design for Unmanned Quadrotor under Faults and Cyber Attacks.” In 25th International Conference on Systems Engineering, Las Vegas, USA. 2017.
- Abbaspour, Alireza, Payam Aboutalebi, Kang K. Yen, and Arman Sargolzaei. “Neural adaptive observer-based sensor and actuator fault detection in nonlinear systems: Application in UAV.” ISA transactions 67 (2017): 317-329.
- Sargolzaei, Arman, Carl D. Crane, Alireza Abbaspour, and Shirin Noei. “A machine learning approach for fault detection in vehicular cyber-physical systems.” In Machine Learning and Applications (ICMLA), 2016 15th IEEE International Conference on, pp. 636-640. IEEE, 2016.
- Abbaspour, Alireza, Kang K. Yen, Shirin Noei, and Arman Sargolzaei. “Detection of fault data injection attack on UAV using adaptive neural network.” Procedia computer science 95 (2016): 193-200.
- Noei, Shirin, Arman Sargolzaei, Alireza Abbaspour, and Kang Yen. “A decision support system for improving resiliency of cooperative adaptive cruise control systems.” Procedia computer science 95 (2016): 489-496.