Browsing by Author "Celdran Martinez, Victor"
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Item Open Access Detect and avoid considerations for safe sUAS operations in urban environments(IEEE, 2021-11-15) Celdran Martinez, Victor; Ince, Bilkan; Kumar Selvam, Praveen; Petrunin, Ivan; Seo, Min-Guk; Anastassacos, Edward; Royall, Paul G.; Cole, Adrian; Tsourdos, Antonios; Knorr, SebastianOperations involving small Unmanned Aerial Systems (sUAS) in urban environments are occurring ever more frequently as recognized applications gain acceptance, and new use cases emerge, such as urban air mobility, medical deliveries, and support of emergency services. Higher demands in these operations and the requirement to access urban airspace present new challenges in sUAS operational safety. The presence of Detect and Avoid (DAA) capability of sUAS is one of the major requirements to its safe operation in urban environments according to the current legislation, such as the CAP 722 in the United Kingdom (UK). The platform or its operator proves a full awareness of all potential obstacles within the mission, maintains a safe distance from other airspace users, and, ultimately, performs Collision Avoidance (CA) maneuvers to avoid imminent impacts. Different missions for the defined scenarios are designed and performed within the simulation model in Software Tool Kit (STK) software environment, covering a wide range of practical cases. The acquired data supports assessment of feasibility and requirements to real-time processing. Analysis of the findings and simulation results leads to a holistic approach to implementation of sUAS operations in urban environments, focusing on extracting critical DAA capability for safe mission completion. The proposed approach forms a valuable asset for safe operations validation, enabling better evaluation of risk mitigation for sUAS urban operations and safety-focused design of the sensor payload and algorithms.Item Open Access Risk assessment for sUAS in urban environments: a comprehensive analysis, modelling and validation for safe operations(AIAA, 2024-01-04) Celdran Martinez, Victor; Shin, Hyo-Sang; Tsourdos, AntoniosThe rapidly growing number of applications for small Unmanned Aerial Systems (sUAS) in last-mile applications within metropolitan environments creates a complex airspace and ground safety scenario, where numerous risks must be considered to accomplish safe operations. The built-up and heterogeneously shaped geometry, together with the densely populated and transited nature of urban scenes, define a challenging scene for piloted and autonomous missions, where operators need to consider performance-based and third-party risks. In response to the increasing requirements inherent from urban scenarios, this paper proposes an integrated and comprehensive risk model for urban sUAS operations, composed by different risk layers designed for real-world scenarios, and validated through simulated drone flights and 3D risk-based navigation. By identifying the different risk requirements for sUAS operations, first party risks – including navigation performance, data link monitoring and collision avoidance – are computed within a photorealistic simulation environment for a discretized airspace representation. On top of this, trajectory based third party risks are modelled to identify potential routes subject to drone failure and consequent fatality and third party damage, as well as societal impact in terms of noise and privacy. Risk-based navigation techniques are implemented to validate the resulting model, including classical path planning and reinforcement learning. The results enable the perception of urban scenes associated risks through the lenses of risk modelling, providing a valuable methodology for sUAS urban operations and contributing to safer drone flights.