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Towards Robust Autonomous Landing Systems: Iterative Solutions and Key Lessons Learned

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arxiv 2505.12176 v2 pith:TU6ELAXW submitted 2025-05-18 cs.RO

Sebastian Schroder , Yao Deng , Alice James , Avishkar Seth , Kye Morton , Subhas Mukhopadhyay , Richard Han , Xi Zheng This is my paper
classification cs.RO
keywords autonomouslandingchallengesdevelopmentiterativerobustsolutionssystems
verification ladder T0 review T1 audit T2 compute T3 formal
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Uncrewed Aerial Vehicles (UAVs) have become a focal point of research, with both established companies and startups investing heavily in their development. This paper presents our iterative process in developing a robust autonomous marker-based landing system, highlighting the key challenges encountered and the solutions implemented. It reviews existing systems for autonomous landing processes, and through this aims to contribute to the community by sharing insights and challenges faced during development and testing.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Regression Testing Optimization for ROS-based Autonomous Systems: A Comprehensive Review of Techniques

    cs.SE 2025-06 conditional novelty 4.0 of 10

    A survey that categorizes 122 papers on regression test optimization and argues ROS-based autonomous systems need new semantic and neurosymbolic approaches.

  2. A Step-by-Step Guide to Creating a Robust Autonomous Drone Testing Pipeline

    cs.SE 2025-06 unverdicted novelty 2.0 of 10

    A four-stage drone testing pipeline guide, illustrated with the authors' marker-based landing system and a review of emerging test automation trends.

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