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Found 5 papers, 3 papers with code
Flexible and Fully Quantized Ultra-Lightweight TinyissimoYOLO for Ultra-Low-Power Edge Systems
With this paper, we demonstrate the suitability and flexibility of TinyissimoYOLO on state-of-the-art detection datasets for real-time ultra-low-power edge inference.
Constructing Metric-Semantic Maps using Floor Plan Priors for Long-Term Indoor Localization
We exploit 3D object detections from monocular RGB frames for both, the object-based map construction, and for globally localizing in the constructed map.
Fully On-board Low-Power Localization with Multizone Time-of-Flight Sensors on Nano-UAVs
Experimental evaluation using a nano-UAV open platform demonstrated that the proposed solution is capable of localizing on a 31. 2m$\boldsymbol{^2}$ map with 0. 15m accuracy and an above 95% success rate.
IR-MCL: Implicit Representation-Based Online Global Localization
The experiments suggest that the presented implicit representation is able to predict more accurate 2D LiDAR scans leading to an improved observation model for our particle filter-based localization.
Training Lightweight CNNs for Human-Nanodrone Proximity Interaction from Small Datasets using Background Randomization
We consider the task of visually estimating the pose of a human from images acquired by a nearby nano-drone; in this context, we propose a data augmentation approach based on synthetic background substitution to learn a lightweight CNN model from a small real-world training set.
