ArduPilot-Based Adaptive Autopilot: Architecture and Software-in-the-Loop Experiments

Baldi, Simone; Sun, Danping; Xia, Xue; Zhou, Guopeng; Liu, Di

doi:10.1109/taes.2022.3162179

Cited by 20 publications

(6 citation statements)

References 41 publications

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“…In the past decade, Ardupilot 17 , a successful open-source autopilot project, has emerged, enabling small robotic systems to perform autonomous missions. Because of its robustness and versatile functionalities, it has been used in numerous scientific and commercial applications ( Baldi et al, 2022 ; Baidya et al, 2018 ; Luo et al, 2019 ). Given the large number of developers, 640 as of Autumn 2022, it has grown to cover different vehicle platforms, including rovers, boats, and different types of aerial robots.…”

Section: Use Cases and The Ground Truthmentioning

confidence: 99%

Building causal models for finding actual causes of unmanned aerial vehicle failures

Zibaei,

Borth

2024

Front. Robot. AI

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Finding actual causes of unmanned aerial vehicle (UAV) failures can be split into two main tasks: building causal models and performing actual causality analysis (ACA) over them. While there are available solutions in the literature to perform ACA, building comprehensive causal models is still an open problem. The expensive and time-consuming process of building such models, typically performed manually by domain experts, has hindered the widespread application of causality-based diagnosis solutions in practice. This study proposes a methodology based on natural language processing for automating causal model generation for UAVs. After collecting textual data from online resources, causal keywords are identified in sentences. Next, cause–effect phrases are extracted from sentences based on predefined dependency rules between tokens. Finally, the extracted cause–effect pairs are merged to form a causal graph, which we then use for ACA. To demonstrate the applicability of our framework, we scrape online text resources of Ardupilot, an open-source UAV controller software. Our evaluations using real flight logs show that the generated graphs can successfully be used to find the actual causes of unwanted events. Moreover, our hybrid cause–effect extraction module performs better than a purely deep-learning based tool (i.e., CiRA) by 32% in precision and 25% in recall in our Ardupilot use case.

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Section: Use Cases and The Ground Truthmentioning

confidence: 99%

Building causal models for finding actual causes of unmanned aerial vehicle failures

Zibaei,

Borth

2024

Front. Robot. AI

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“…Ardupilot is an open-source autopilot software designed to control UAVs and other autonomous systems [ 236 , 237 , 238 , 239 ].…”

Section: Uavs Softwarementioning

confidence: 99%

A Review on the State of the Art in Copter Drones and Flight Control Systems

Peksa,

Mamchur

2024

Sensors

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This paper presents an overview on the state of the art in copter drones and their components. It starts by providing an introduction to unmanned aerial vehicles in general, describing their main types, and then shifts its focus mostly to multirotor drones as the most attractive for individual and research use. This paper analyzes various multirotor drone types, their construction, typical areas of implementation, and technology used underneath their construction. Finally, it looks at current challenges and future directions in drone system development, emerging technologies, and future research topics in the area. This paper concludes by highlighting some key challenges that need to be addressed before widespread adoption of drone technologies in everyday life can occur. By summarizing an up-to-date survey on the state of the art in copter drone technology, this paper will provide valuable insights into where this field is heading in terms of progress and innovation.

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“…Is an open source autopilot platform [326] used for autonomous navigation and control applications, which supports a variety of UAVs, including fixed-wing aircraft, multi-rotors, and rovers. The platform provides advanced control algorithms, such as adaptive control and AI [222,270], that can be used to improve the stability and performance of UAVs [218]. It provides a range of features for autonomous navigation and control, including GPS waypoint navigation, automated takeoff and landing, and mission planning.…”

Section: Ardupilotmentioning

confidence: 99%

A Comprehensive Review of Recent Research Trends on Unmanned Aerial Vehicles (UAVs)

Telli,

Kraa,

Himeur

et al. 2023

Systems

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The growing interest in unmanned aerial vehicles (UAVs) from both the scientific and industrial sectors has attracted a wave of new researchers and substantial investments in this expansive field. However, due to the wide range of topics and subdomains within UAV research, newcomers may find themselves overwhelmed by the numerous options available. It is therefore crucial for those involved in UAV research to recognize its interdisciplinary nature and its connections with other disciplines. This paper presents a comprehensive overview of the UAV field, highlighting recent trends and advancements. Drawing on recent literature reviews and surveys, the review begins by classifying UAVs based on their flight characteristics. It then provides an overview of current research trends in UAVs, utilizing data from the Scopus database to quantify the number of scientific documents associated with each research direction and their interconnections. This paper also explores potential areas for further development in UAVs, including communication, artificial intelligence, remote sensing, miniaturization, swarming and cooperative control, and transformability. Additionally, it discusses the development of aircraft control, commonly used control techniques, and appropriate control algorithms in UAV research. Furthermore, this paper addresses the general hardware and software architecture of UAVs, their applications, and the key issues associated with them. It also provides an overview of current open source software and hardware projects in the UAV field. By presenting a comprehensive view of the UAV field, this paper aims to enhance our understanding of this rapidly evolving and highly interdisciplinary area of research.

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ArduPilot-Based Adaptive Autopilot: Architecture and Software-in-the-Loop Experiments

Abstract: This article presents an adaptive method for ArduPilot-based autopilots of fixed-wing unmanned aerial vehicles (UAVs). ArduPilot is a popular open-source unmanned vehicle software suite. We explore Manuscript

Cited by 20 publications

References 41 publications

Building causal models for finding actual causes of unmanned aerial vehicle failures

Building causal models for finding actual causes of unmanned aerial vehicle failures

A Review on the State of the Art in Copter Drones and Flight Control Systems

A Comprehensive Review of Recent Research Trends on Unmanned Aerial Vehicles (UAVs)

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