Automated system-level testing of unmanned aerial systems

被引:2
|
作者
Sartaj, Hassan [1 ]
Muqeet, Asmar [2 ]
Iqbal, Muhammad Zohaib [2 ]
Khan, Muhammad Uzair [1 ]
机构
[1] Natl Univ Comp & Emerging Sci, Dept Comp Sci, AK Brohi Rd, Islamabad, Pakistan
[2] Quest Lab, I8 Markaz, Islamabad, Pakistan
关键词
Artificial intelligence; Deep reinforcement learning; Unmanned aerial systems; UAV; Drones; GCS; Testing automation; FLIGHT;
D O I
10.1007/s10515-024-00462-9
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Unmanned aerial systems (UAS) rely on various avionics systems that are safety-critical and mission-critical. A major requirement of international safety standards is to perform rigorous system-level testing of avionics software systems. The current industrial practice is to manually create test scenarios, manually/automatically execute these scenarios using simulators, and manually evaluate outcomes. The test scenarios typically consist of setting certain flight or environment conditions and testing the system under test in these settings. The state-of-the-art approaches for this purpose also require manual test scenario development and evaluation. In this paper, we propose a novel approach to automate the system-level testing of the UAS. The proposed approach (namely AITester) utilizes model-based testing and artificial intelligence (AI) techniques to automatically generate, execute, and evaluate various test scenarios. The test scenarios are generated on the fly, i.e., during test execution based on the environmental context at runtime. The approach is supported by a toolset. We empirically evaluated the proposed approach on two core components of UAS, an autopilot system of an unmanned aerial vehicle (UAV) and cockpit display systems (CDS) of the ground control station (GCS). The results show that the AITester effectively generates test scenarios causing deviations from the expected behavior of the UAV autopilot and reveals potential flaws in the GCS-CDS.
引用
收藏
页数:48
相关论文
共 50 条
  • [21] Optimized structural inspection path planning for automated unmanned aerial systems
    Zhao, Yuxiang
    Lu, Benhao
    Alipour, Mohamad
    AUTOMATION IN CONSTRUCTION, 2024, 168
  • [22] Conservative Algorithms for Automated Collision Awareness for Multiple Unmanned Aerial Systems
    Ueunten, Kevin
    Lum, Christopher
    Creigh, Al
    Tsujita, Keisuke
    2015 IEEE AEROSPACE CONFERENCE, 2015,
  • [23] System-Level Performance Analysis of Cooperative Multiple Unmanned Aerial Vehicles for Wildfire Surveillance Using Agent-Based Modeling
    Maqbool, Ayesha
    Mirza, Alina
    Afzal, Farkhanda
    Shah, Tajammul
    Khan, Wazir Zada
    Bin Zikria, Yousaf
    Kim, Sung Won
    SUSTAINABILITY, 2022, 14 (10)
  • [24] A Study Examining the Adverse Effects of Electromagnetic Pulse on System-Level Unmanned Aerial Vehicles and Their Subsequent Damage Assessment and Mitigation Strategies
    Qiao, Zhijun
    Pan, Xuchao
    He, Yong
    Zhang, Jiangnan
    Yu, Hao
    Geng, Chang
    IRANIAN JOURNAL OF CHEMISTRY & CHEMICAL ENGINEERING-INTERNATIONAL ENGLISH EDITION, 2024, 43 (11): : 4185 - 4199
  • [25] Unmanned aerial system for antenna measurement and diagnosis: evaluation and testing
    Garcia-Fernandez, Maria
    Alvarez Lopez, Yuri
    Las-Heras Andres, Fernando
    IET MICROWAVES ANTENNAS & PROPAGATION, 2019, 13 (13) : 2224 - 2231
  • [26] Automated Situation Analysis as Next Level of Unmanned Aerial Vehicle Artificial Intelligence
    Strupka, Gunta
    Levchenkov, Anatoly
    Gorobetz, Mikhail
    ADVANCES IN HUMAN FACTORS IN SIMULATION AND MODELING (AHFE 2017), 2018, 591 : 25 - 37
  • [27] Development of a Health Monitoring System for Unmanned Aerial Systems
    Hahn, Jason
    Kaabouch, Naima
    Foerster, Kyle
    2014 IEEE AEROSPACE CONFERENCE, 2014,
  • [28] Development of Unmanned Transport System for Automated Systems
    Cho, Hyunhak
    Yu, Jungwon
    Jeong, Yeongsang
    Lee, Hansoo
    Kim, Sungshin
    PROCEEDINGS OF INTERNATIONAL CONFERENCE ON ARTIFICIAL LIFE AND ROBOTICS (ICAROB2015), 2015, : 52 - 55
  • [30] Supporting system-level testing of applications by active real-time database systems
    Mellin, J
    ACTIVE, REAL-TIME, AND TEMPORAL DATABASE SYSTEMS, PROCEEDINGS, 1998, 1553 : 194 - 211