HUNT: High-Speed UAV Navigation and Tracking in Unstructured Environments via Instantaneous Relative Frames

• URL: http://arxiv.org/abs/2509.19452v3
• Date: Sun, 28 Sep 2025 18:17:18 GMT
• Title: HUNT: High-Speed UAV Navigation and Tracking in Unstructured Environments via Instantaneous Relative Frames
• Abstract summary: HUNT (High-speed UAV Navigation and Tracking) is a real-time framework that unifies, acquisition, and tracking within a single relative formulation.<n>Trials in dense forests, container compounds, and search-and-rescue operations with vehicles and mannequins demonstrate robust autonomy where global methods fail.
• Score: 50.83645076723809
• License: http://creativecommons.org/publicdomain/zero/1.0/
• Abstract: Search and rescue operations require unmanned aerial vehicles to both traverse unknown unstructured environments at high speed and track targets once detected. Achieving both capabilities under degraded sensing and without global localization remains an open challenge. Recent works on relative navigation have shown robust tracking by anchoring planning and control to a visible detected object, but cannot address navigation when no target is in the field of view. We present HUNT (High-speed UAV Navigation and Tracking), a real-time framework that unifies traversal, acquisition, and tracking within a single relative formulation. HUNT defines navigation objectives directly from onboard instantaneous observables such as attitude, altitude, and velocity, enabling reactive high-speed flight during search. Once a target is detected, the same perception-control pipeline transitions seamlessly to tracking. Outdoor experiments in dense forests, container compounds, and search-and-rescue operations with vehicles and mannequins demonstrate robust autonomy where global methods fail.

Related papers

• DynFly: Dynamic-Aware Continuous Trajectory Generation for UAV Vision-Language Navigation in Urban Environments [55.73595346639892]
  We propose DynFly to bridge high-level navigation reasoning and executable UAV motion.<n>DynFly represents expert trajectories in B-spline control-point space and employs a Spline-DiT generator to learn conditional trajectory generation.<n>Experiments on the OpenUAV UAV-VLN benchmark show that DynFly improves both navigation performance and trajectory quality.
  arXiv  Detail & Related papers  (2026-06-30T13:33:48Z)
• AUSLUN: A Fixed-Hover UAV--USV System for GNSS-Denied Maritime Search and Navigation [7.220023631779745]
  Global navigation satellite system (GNSS) denial can prevent an unmanned surface vehicle (USV) from both finding a distant vessel and maintaining a globally referenced approach.<n>This paper presents AUSLUN, a fixed-hover aerial-surface system that uses a coastal unmanned aerial vehicle (UAV) as a long-range sensing and navigation anchor.<n>Results establish the feasibility and operating boundary of fixed-hover UAV assistance for stationary-target approach in coastal-denied environments.
  arXiv  Detail & Related papers  (2026-06-29T07:15:59Z)
• AgenticDiffusion: Agentic Diffusion-based Path Planning for Vision-Based UAV Navigation [2.186077977059593]
  Indoor UAV navigation requires efficient exploration, scene understanding, and reliable trajectory execution under limited field-of-view observations.<n>We propose AgenticDiffusion, a multi-view UAV navigation framework that coordinates language-guided reasoning, open-vocabulary target grounding, vision-based diffusion planning, and NMPC.<n>The framework was validated in four real-world UAV navigation scenarios involving adaptive viewpoint selection, multi-stage mission execution, long-horizon navigation, and safe landing-site selection.
  arXiv  Detail & Related papers  (2026-06-02T18:18:35Z)
• FU-MPC: Frontier- and Uncertainty-Aware Model Predictive Control for Efficient and Accurate UAV Exploration with Motorized LiDAR [29.924596251375892]
  We develop a UAV platform equipped with an independently actuated rotating LiDAR and propose a hierarchical exploration framework.<n>Fu-MPC serves as a local receding-horizon scan controller that optimize LiDAR rotation along the predicted flight trajectory.<n>Experiments in complex environments demonstrate that the proposed system improves exploration efficiency while maintaining robust localization performance.
  arXiv  Detail & Related papers  (2026-05-14T14:54:29Z)
• Beyond Matching to Tiles: Bridging Unaligned Aerial and Satellite Views for Vision-Only UAV Navigation [51.286599397552756]
  We present Bearing-UAV, a vision-driven cross-view navigation method that jointly predicts UAV absolute location and heading from neighboring features.<n>We also present Bearing-UAV-90k, a benchmark for evaluating cross-view localization and navigation.
  arXiv  Detail & Related papers  (2026-03-23T16:17:39Z)
• GL-DT: Multi-UAV Detection and Tracking with Global-Local Integration [0.6299766708197883]
  This paper proposes the Global-Local Detection and Tracking (GL-DT) framework.<n>It employs a Spatio-Temporal Feature Fusion (STFF) module to jointly model motion and appearance features, combined with a global-local collaborative detection strategy.<n> Experimental results demonstrate that the proposed approach significantly improves the continuity and stability of MOT while maintaining real-time performance.
  arXiv  Detail & Related papers  (2025-10-10T07:37:38Z)
• Sight Over Site: Perception-Aware Reinforcement Learning for Efficient Robotic Inspection [57.37596278863949]
  In this work, we revisit inspection from a perception-aware perspective.<n>We propose an end-to-end reinforcement learning framework that explicitly incorporates target visibility as the primary objective.<n>We show that our method outperforms existing classical and learning-based navigation approaches.
  arXiv  Detail & Related papers  (2025-09-22T15:14:02Z)
• 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)
• Ensuring UAV Safety: A Vision-only and Real-time Framework for Collision Avoidance Through Object Detection, Tracking, and Distance Estimation [16.671696289301625]
  This paper presents a deep-learning framework that utilizes optical sensors for the detection, tracking, and distance estimation of non-cooperative aerial vehicles. In this work, we propose a method for estimating the distance information of a detected aerial object in real time using only the input of a monocular camera.
  arXiv  Detail & Related papers  (2024-05-10T18:06:41Z)
• Angle Robustness Unmanned Aerial Vehicle Navigation in GNSS-Denied Scenarios [66.05091704671503]
  We present a novel angle navigation paradigm to deal with flight deviation in point-to-point navigation tasks. We also propose a model that includes the Adaptive Feature Enhance Module, Cross-knowledge Attention-guided Module and Robust Task-oriented Head Module.
  arXiv  Detail & Related papers  (2024-02-04T08:41:20Z)
• A Multi-UAV System for Exploration and Target Finding in Cluttered and GPS-Denied Environments [68.31522961125589]
  We propose a framework for a team of UAVs to cooperatively explore and find a target in complex GPS-denied environments with obstacles. The team of UAVs autonomously navigates, explores, detects, and finds the target in a cluttered environment with a known map. Results indicate that the proposed multi-UAV system has improvements in terms of time-cost, the proportion of search area surveyed, as well as successful rates for search and rescue missions.
  arXiv  Detail & Related papers  (2021-07-19T12:54:04Z)
• Active Visual Information Gathering for Vision-Language Navigation [115.40768457718325]
  Vision-language navigation (VLN) is the task of entailing an agent to carry out navigational instructions inside photo-realistic environments. One of the key challenges in VLN is how to conduct a robust navigation by mitigating the uncertainty caused by ambiguous instructions and insufficient observation of the environment. This work draws inspiration from human navigation behavior and endows an agent with an active information gathering ability for a more intelligent VLN policy.
  arXiv  Detail & Related papers  (2020-07-15T23:54:20Z)
• Reinforcement Learning for UAV Autonomous Navigation, Mapping and Target Detection [36.79380276028116]
  We study a joint detection, mapping and navigation problem for a single unmanned aerial vehicle (UAV) equipped with a low complexity radar and flying in an unknown environment. The goal is to optimize its trajectory with the purpose of maximizing the mapping accuracy and to avoid areas where measurements might not be sufficiently informative from the perspective of a target detection.
  arXiv  Detail & Related papers  (2020-05-05T20:39:18Z)
• Dynamic Radar Network of UAVs: A Joint Navigation and Tracking Approach [36.587096293618366]
  An emerging problem is to track unauthorized small unmanned aerial vehicles (UAVs) hiding behind buildings. This paper proposes the idea of a dynamic radar network of UAVs for real-time and high-accuracy tracking of malicious targets.
  arXiv  Detail & Related papers  (2020-01-13T23:23:09Z)

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.