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On the Accuracy of Near-Optimal CPU-Based Path Planning for UAVs., , and . SCOPES, page 85-88. ACM, (2017)Fully Onboard AI-Powered Human-Drone Pose Estimation on Ultralow-Power Autonomous Flying Nano-UAVs., , , , , , , , and . IEEE Internet Things J., 9 (3): 1913-1929 (2022)Automated Tuning of End-to-end Neural Flight Controllers for Autonomous Nano-drones., , , and . AICAS, page 1-4. IEEE, (2021)GPU-Accelerated Real-Time Path Planning and the Predictable Execution Model., , , and . ICCS, volume 108 of Procedia Computer Science, page 2428-2432. Elsevier, (2017)Extending the Lifetime of Nano-Blimps via Dynamic Motor Control., , , , , and . J. Signal Process. Syst., 91 (3-4): 339-361 (2019)Energy-Efficient, Precise UWB-Based 3-D Localization of Sensor Nodes With a Nano-UAV., , , and . IEEE Internet Things J., 10 (7): 5760-5777 (April 2023)Ultra-low Power Deep Learning-based Monocular Relative Localization Onboard Nano-quadrotors., , , , and . ICRA, page 3411-3417. IEEE, (2023)Vision-State Fusion: Improving Deep Neural Networks for Autonomous Robotics., , , , and . CoRR, (2022)Fünfiiber-Drone: A Modular Open-Platform 18-grams Autonomous Nano-Drone., , , , and . DATE, page 1610-1615. IEEE, (2021)Tiny-PULP-Dronets: Squeezing Neural Networks for Faster and Lighter Inference on Multi-Tasking Autonomous Nano-Drones., , , , , , and . AICAS, page 287-290. IEEE, (2022)