Skyshield: Event-Driven Submillimetre Thin Obstacle Detection for Drone Flight Safety

• URL: http://arxiv.org/abs/2508.09397v2
• Date: Wed, 17 Sep 2025 02:06:05 GMT
• Title: Skyshield: Event-Driven Submillimetre Thin Obstacle Detection for Drone Flight Safety
• Abstract summary: This paper introduces SkyShield, an event-driven, end-to-end framework designed for the perception of submillimeter scale obstacles.<n>Our method employs a lightweight U-Net architecture and an innovative Dice-Contour Regularization Loss to ensure precise detection.
• Score: 22.778033892271555
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Drones operating in complex environments face a significant threat from thin obstacles, such as steel wires and kite strings at the submillimeter level, which are notoriously difficult for conventional sensors like RGB cameras, LiDAR, and depth cameras to detect. This paper introduces SkyShield, an event-driven, end-to-end framework designed for the perception of submillimeter scale obstacles. Drawing upon the unique features that thin obstacles present in the event stream, our method employs a lightweight U-Net architecture and an innovative Dice-Contour Regularization Loss to ensure precise detection. Experimental results demonstrate that our event-based approach achieves mean F1 Score of 0.7088 with a low latency of 21.2 ms, making it ideal for deployment on edge and mobile platforms.

Related papers

• Robust Slip Detection and Material Classification via Spatiotemporal Transformers on a Uniformly-Illuminated Visuo-Tactile Sensor [52.33204893988409]
  We propose a visuo-tactile sensor featuring customized uniform illumination, alongside a unified perception framework.<n>The proposed hardware-software framework provides high-fidelity feedback and a powerful multi-modal perception baseline for complex robotic manipulation.
  arXiv  Detail & Related papers  (2026-08-25T07:25:27Z)
• LCMamNet: A Lightweight Cross-scale Mamba Network for Infrared Small Target Detection [53.811713750107934]
  We propose LCMamNet, a lightweight cross-scale Mamba network for infrared small target detection.<n>A compact hierarchical encoder with cross-shaped directional bottleneck residual blocks strengthens direction-sensitive target structures.<n>Experiments on IRSTD-1k, NUAA-SIRST, and NUDT-SIRST show that the proposed network achieves mIoU scores of 71.25%, 79.60%, and 95.58%, respectively.
  arXiv  Detail & Related papers  (2026-07-27T09:06:14Z)
• TRISTAR: Triple-Signal Stair Recognition and Vision-Only Indoor Navigation for Search-and-Rescue Micro-UAVs [0.0]
  This paper presents a complete autonomous indoor navigation framework for low-cost unmanned aerial vehicles based exclusively on monocular vision.<n>The framework consists of two independent behaviors: (i) corridor exploration with automatic door detection, room entry, OCR-based room identification, and victim inspection; and (ii) autonomous stair ascent based on TRISTAR.
  arXiv  Detail & Related papers  (2026-07-04T11:06:00Z)
• NightSight: Passive Computation for Navigation in Dark Using Events [3.7376797687484005]
  Small aerial robots are well-suited for search and rescue in confined and hazardous environments.<n>We present a lightweight perception approach that combines a monocular event camera, a coded aperture lens, and an infrared dot projector.<n>Our system operates in real time at 20 Hz on a NVIDIA Jetson Orin Nano, demonstrating suitability for resource-constrained platforms.
  arXiv  Detail & Related papers  (2026-05-25T21:07:44Z)
• KIO-planner: Attention-Guided Single-Stage Motion Planning with Dual Mapping for UAV Navigation [12.009002689122374]
  KIO-planner is an attention-guided single-stage trajectory planning framework.<n>New Dual Mapping mechanism enforces kinodynamic feasibility and collision-free flight without global map fusion.
  arXiv  Detail & Related papers  (2026-05-19T11:41:23Z)
• Instance-level Visual Active Tracking with Occlusion-Aware Planning [61.982298426203165]
  Visual Active Tracking (VAT) aims to control cameras to follow a target in 3D space.<n>VAT faces two key bottlenecks in real-world deployment: confusion from visually similar distractors and severe failure under occlusions.<n>We propose OA-VAT, a unified pipeline with three complementary modules.
  arXiv  Detail & Related papers  (2026-04-23T09:11:50Z)
• ImpedanceDiffusion: Diffusion-Based Global Path Planning for UAV Swarm Navigation with Generative Impedance Control [1.9182058480922208]
  ImpedanceDiffusion is a hierarchical framework for safe swarm navigation in cluttered indoor environments.<n>The framework generates geometric global trajectories directly from RGB images without explicit map construction.<n>It achieves a 92% success rate while maintaining stable impedance-based formation control with bounded oscillations and no in-flight collisions.
  arXiv  Detail & Related papers  (2026-03-10T00:06:55Z)
• SCAFusion: A Multimodal 3D Detection Framework for Small Object Detection in Lunar Surface Exploration [18.857802421595235]
  This paper presents SCAFusion, a multimodal 3D object detection model tailored for lunar robotic missions.<n>With negligible increase in parameters, our model achieves 69.7% mAP and 72.1% NDS on the nuScenes validation set.<n>In simulated lunar environments built on Isaac Sim, SCAFusion achieves 90.93% mAP, outperforming the baseline by 11.5%.
  arXiv  Detail & Related papers  (2025-12-27T07:08:03Z)
• RoboTracer: Mastering Spatial Trace with Reasoning in Vision-Language Models for Robotics [53.053660003572965]
  We propose RoboTracer, a 3D-aware VLM that first achieves both 3D spatial referring and measuring.<n>RoboTracer advances multi-step metric-grounded reasoning via reinforcement fine-tuning.<n>We present TraceSpatial-Bench, a challenging benchmark to evaluate spatial tracing.
  arXiv  Detail & Related papers  (2025-12-15T18:52:43Z)
• Autonomous Navigation of Cloud-Controlled Quadcopters in Confined Spaces Using Multi-Modal Perception and LLM-Driven High Semantic Reasoning [0.0]
  This paper introduces an advanced AI-driven perception system for autonomous navigation in GPS-denied indoor environments.<n>System integrates YOLOv11 for object detection, Depth Anything V2 for monocular depth estimation, a PCB equipped with Time-of-Flight (ToF) sensors and an Inertial Measurement Unit (IMU)<n> Experimental results in an indoor testbed demonstrate strong performance, with object detection achieving a mean Average Precision (mAP50) of 0.6, depth estimation Mean Absolute Error (MAE) of 7.2 cm, and end-to-end system latency below 1 second.
  arXiv  Detail & Related papers  (2025-08-11T12:00:03Z)
• NOVA: Navigation via Object-Centric Visual Autonomy for High-Speed Target Tracking in Unstructured GPS-Denied Environments [56.35569661650558]
  We introduce NOVA, a fully onboard, object-centric framework that enables robust target tracking and collision-aware navigation.<n>Rather than constructing a global map, NOVA formulates perception, estimation, and control entirely in the target's reference frame.<n>We validate NOVA across challenging real-world scenarios, including urban mazes, forest trails, and repeated transitions through buildings with intermittent GPS loss.
  arXiv  Detail & Related papers  (2025-06-23T14:28:30Z)
• Monocular Obstacle Avoidance Based on Inverse PPO for Fixed-wing UAVs [29.207513994002202]
  Fixed-wing Unmanned Aerial Vehicles (UAVs) are one of the most commonly used platforms for the Low-altitude Economy (LAE) and Urban Air Mobility (UAM)<n>Classical obstacle avoidance systems, which rely on prior maps or sophisticated sensors, face limitations in unknown low-altitude environments and small UAV platforms.<n>This paper proposes a lightweight deep reinforcement learning (DRL) based UAV collision avoidance system.
  arXiv  Detail & Related papers  (2024-11-27T03:03:37Z)
• HazyDet: Open-Source Benchmark for Drone-View Object Detection with Depth-Cues in Hazy Scenes [54.24350833692194]
  HazyDet is the first, large-scale benchmark specifically designed for drone-view object detection in hazy conditions.<n>We propose the Depth-Conditioned Detector (DeCoDet) to address the severe visual degradation induced by haze.<n>HazyDet provides a challenging and realistic testbed for advancing detection algorithms.
  arXiv  Detail & Related papers  (2024-09-30T00:11:40Z)
• ODTFormer: Efficient Obstacle Detection and Tracking with Stereo Cameras Based on Transformer [12.58804521609764]
  ODTFormer is a Transformer-based model to address both obstacle detection and tracking problems. We report comparable accuracy to state-of-the-art obstacle tracking models while requiring only a fraction of their cost.
  arXiv  Detail & Related papers  (2024-03-21T17:59:55Z)
• Global Context Aggregation Network for Lightweight Saliency Detection of Surface Defects [70.48554424894728]
  We develop a Global Context Aggregation Network (GCANet) for lightweight saliency detection of surface defects on the encoder-decoder structure. First, we introduce a novel transformer encoder on the top layer of the lightweight backbone, which captures global context information through a novel Depth-wise Self-Attention (DSA) module. The experimental results on three public defect datasets demonstrate that the proposed network achieves a better trade-off between accuracy and running efficiency compared with other 17 state-of-the-art methods.
  arXiv  Detail & Related papers  (2023-09-22T06:19:11Z)
• Multi-Modal Neural Radiance Field for Monocular Dense SLAM with a Light-Weight ToF Sensor [58.305341034419136]
  We present the first dense SLAM system with a monocular camera and a light-weight ToF sensor. We propose a multi-modal implicit scene representation that supports rendering both the signals from the RGB camera and light-weight ToF sensor. Experiments demonstrate that our system well exploits the signals of light-weight ToF sensors and achieves competitive results.
  arXiv  Detail & Related papers  (2023-08-28T07:56:13Z)
• Vision Guided MIMO Radar Beamforming for Enhanced Vital Signs Detection in Crowds [26.129503530877006]
  We develop a novel dual-sensing system, in which a vision sensor is leveraged to guide digital beamforming in a radar. The calibrated dual system achieves about two centimeters precision in three-dimensional space within a field of view of $75circ$ by $65circ$ and for a range of two meters.
  arXiv  Detail & Related papers  (2023-06-18T10:09:16Z)
• Efficient and Robust LiDAR-Based End-to-End Navigation [132.52661670308606]
  We present an efficient and robust LiDAR-based end-to-end navigation framework. We propose Fast-LiDARNet that is based on sparse convolution kernel optimization and hardware-aware model design. We then propose Hybrid Evidential Fusion that directly estimates the uncertainty of the prediction from only a single forward pass.
  arXiv  Detail & Related papers  (2021-05-20T17:52:37Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.