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  • Fast Swarming of UAVs in GNSS-denied Feature-poor Environments without . . .
    A decentralized swarm approach for the fast cooperative flight of Unmanned Aerial Vehicles (UAVs) in feature-poor environments without any external localization and communication is introduced in this paper
  • Emergent Swarm Solutions
    Website Emergent Swarm Solutions, company focused on autonomy and swarming software for drones Collision avoidance, path planning, GNSS-denied, GPS-denied
  • Autonomous Navigation for Drone Swarms in GPS-Denied Environments Using . . .
    Operating in these ‘GPS denied’ environments poses a new challenge; both in navigation, and in collision avoidance This study proposes two novel concepts; a structural model of environmental deviance to aid in autonomous navigation, and a method to use the output of said model to implement a collision avoidance system
  • SmrtSwarm : A Novel Swarming Model for Real-World Environments - MDPI
    It is the first comprehensive model that enables swarming in all kinds of decentralized environments regardless of GPS signal availability and obstacles We achieve this by using a stereo camera and a novel algorithm that quickly identifies drones in depth maps and infers their velocities and identities with reference to itself
  • AI Drone Swarm Coordination: 20 Advances (2025) - Yenra
    Shield AI’s 2024 Hivemind trials navigated multiple V-BAT drones through smoke-filled, GPS-denied environments with under 1 m positioning error over 2 km flights (Shield AI, 2024) Nguyen, Lee, and Park (2023) achieved 95% localization accuracy in an underground mine using collaborative SLAM among five drones (Sensors, 23(15), 7176)
  • Autonomous Navigation for Drone Swarms in GPS-Denied Environments using . . .
    safely navigate a swarm of drones in a GPS-denied environment with a purpose-fully simpli ed set of sensor modalities and computational capabilities This framework is shown to provide course maintenance and collision avoidance via structural learning of environmental deviance’s in an online manner To sup-
  • SmrtSwarm: A Novel Swarming Model for Real-World Environments - IIT Delhi
    Our proposed solution SmrtSwarm 15 solves all of these problems It is the first comprehensive model that enables swarming in all kinds 16 of decentralized environments regardless of GPS signal availability and obstacles
  • Humancyyborg Drooid-Drone-swarm-Algorithm - GitHub
    GitHub - Humancyyborg Drooid-Drone-swarm-Algorithm: We demonstrate decentralized drone swarm control learned via large-scale multi-agent reinforcement learning Cannot retrieve latest commit at this time A codebase for training reinforcement learning policies for quadrotor swarms Includes: Paper: https: arxiv org abs 2109 07735
  • The Dawn of Decentralized Control Algorithms for Drone Swarms - fxis. ai
    A team of researchers at MIT has been working on a revolutionary control algorithm that not only promises to enhance the coordination of drones but also tackles the significant problem of avoiding collisions with both stationary and moving obstacles
  • OMNInav: A Breakthrough in GPS-Denied Navigation for UAS
    OMNInav is a core component of the OMNISCIENCE TM drone autonomy framework, delivering precise, real-time, multi-modality positional awareness to enable autonomous operations in GPS-denied environments





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