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In this paper, we address the vision-based autonomous landing problem in complex urban environments using deep neural networks for semantic segmentation and risk assessment. We propose employing the SegFormer, a state-of-the-art visual…

Landing safely in crowded urban environments remains an essential yet challenging endeavor for Unmanned Aerial Vehicles (UAVs), especially in emergency situations. In this work, we propose a risk-aware approach that harnesses semantic…

Mobile robots navigating in indoor and outdoor environments must be able to identify and avoid unsafe terrain. Although a significant amount of work has been done on the detection of standing obstacles (solid obstructions), not much work…

Computer Vision and Pattern Recognition · Computer Science 2019-02-05 Anish Singhani

Autonomous landing of Unmanned Aerial Vehicles (UAVs) in crowded scenarios is crucial for successful deployment of UAVs in populated areas, particularly in emergency landing situations where the highest priority is to avoid hurting people.…

Robotics · Computer Science 2022-03-01 Javier González-Trejo , Diego Mercado-Ravell , Israel Becerra , Rafael Murrieta-Cid

Autonomous drone delivery systems are rapidly advancing, but ensuring safe and reliable package drop-offs remains highly challenging in cluttered urban and suburban environments where accurately identifying suitable package drop zones is…

Computer Vision and Pattern Recognition · Computer Science 2026-04-16 Mahyar Ghazanfari , Peng Wei

Safe autonomous landing for Unmanned Aerial Vehicles (UAVs) in populated areas is a crucial aspect for successful urban deployment, particularly in emergency landing situations. Nonetheless, validating autonomous landing in real scenarios…

Semantic segmentation is a crucial task for robot navigation and safety. However, it requires huge amounts of pixelwise annotations to yield accurate results. While recent progress in computer vision algorithms has been heavily boosted by…

Computer Vision and Pattern Recognition · Computer Science 2019-10-23 Alina Marcu , Dragos Costea , Vlad Licaret , Marius Leordeanu

In recent years, consumer Unmanned Aerial Vehicles have become very popular, everyone can buy and fly a drone without previous experience, which raises concern in regards to regulations and public safety. In this paper, we present a novel…

Robotics · Computer Science 2016-02-29 Thomas Castelli , Aidean Sharghi , Don Harper , Alain Tremeau , Mubarak Shah

The escalating use of Unmanned Aerial Vehicles (UAVs) as remote sensing platforms has garnered considerable attention, proving invaluable for ground object recognition. While satellite remote sensing images face limitations in resolution…

Computer Vision and Pattern Recognition · Computer Science 2025-10-29 Vlatko Spasev , Ivica Dimitrovski , Ivan Chorbev , Ivan Kitanovski

This paper presents a vision-only autonomous flight system for small UAVs operating in controlled indoor environments. The system combines semantic segmentation with monocular depth estimation to enable obstacle avoidance, scene…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Sebastian Mocanu , Emil Slusanschi , Marius Leordeanu

Unmanned Aerial Vehicles (UAVs) hold immense potential for critical applications, such as search and rescue operations, where accurate perception of indoor environments is paramount. However, the concurrent amalgamation of localization, 3D…

Robotics · Computer Science 2024-01-17 Thanh Nguyen Canh , Van-Truong Nguyen , Xiem HoangVan , Armagan Elibol , Nak Young Chong

Localization is one of the most crucial tasks for Unmanned Aerial Vehicle systems (UAVs) directly impacting overall performance, which can be achieved with various sensors and applied to numerous tasks related to search and rescue…

Robotics · Computer Science 2024-11-05 Thanh Nguyen Canh , Huy-Hoang Ngo , Xiem HoangVan , Nak Young Chong

For navigation of robots, image segmentation is an important component to determining a terrain's traversability. For safe and efficient navigation, it is key to assess the uncertainty of the predicted segments. Current uncertainty…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Judith Dijk , Gertjan Burghouts , Kapil D. Katyal , Bryanna Y. Yeh , Craig T. Knuth , Ella Fokkinga , Tejaswi Kasarla , Pascal Mettes

A remaining challenge in multirotor drone flight is the autonomous identification of viable landing sites in unstructured environments. One approach to solve this problem is to create lightweight, appearance-based terrain classifiers that…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Joshua Springer , Gylfi Þór Guðmundsson , Marcel Kyas

Autonomous landing of uncrewed aerial vehicles (UAVs) in unknown, dynamic environments poses significant safety challenges, particularly near people and infrastructure, as UAVs transition to routine urban and rural operations. Existing…

Robotics · Computer Science 2026-03-19 Markus Gross , Andreas Greiner , Sai Bharadhwaj Matha , Felix Soest , Daniel Cremers , Henri Meeß

Camera-equipped unmanned vehicles (UVs) have received a lot of attention in data collection for construction monitoring applications. To develop an autonomous platform, the UV should be able to process multiple modules (e.g.,…

Robotics · Computer Science 2019-01-28 Khashayar Asadi , Pengyu Chen , Kevin Han , Tianfu Wu , Edgar Lobaton

The remarkable growth of unmanned aerial vehicles (UAVs) has also sparked concerns about safety measures during their missions. To advance towards safer autonomous aerial robots, this work presents a vision-based solution to ensuring safe…

Robotics · Computer Science 2023-10-09 Phuoc Nguyen Thuan , Tomi Westerlund , Jorge Peña Queralta

Demand for fast and economical parcel deliveries in urban environments has risen considerably in recent years. A framework envisions efficient last-mile delivery in urban environments by leveraging a network of ride-sharing vehicles, where…

Robotics · Computer Science 2021-03-16 Gabriel Barsi Haberfeld , Aditya Gahlawat , Naira Hovakimyan

Unmanned aerial vehicles (UAVs) are often used for navigating dangerous terrains, however they are difficult to pilot. Due to complex input-output mapping schemes, limited perception, the complex system dynamics and the need to maintain a…

Robotics · Computer Science 2021-03-02 Kal Backman , Dana Kulić , Hoam Chung

In this paper, a simple technique for Unmanned Aerial Vehicles (UAVs) potential landing site detection using terrain information through identification of flat areas, is presented. The algorithm utilizes digital elevation models (DEM) that…

Computer Vision and Pattern Recognition · Computer Science 2021-07-16 Efstratios Kakaletsis , Nikos Nikolaidis
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