2 citations · 2 across the 7 of their papers we have counts for
5 papers · 1 filter
MAC-I: Learned Metrics-Aware Covariance for Robust Visual-Inertial Fusion in Initialization and Calibration
Xiang Fei, Yuheng Qiu, Can Xu +5
Visual-Inertial (VI) fusion is fundamental to accurate and robust state estimation, where camera and IMU measurements are combined according to their respective uncertainties. Exis…
RAVEN: Resilient Aerial Navigation via Open-Set Semantic Memory and Behavior Adaptation
Seungchan Kim, Omar Alama, Dmytro Kurdydyk +5
Aerial outdoor semantic navigation requires robots to explore large, unstructured environments to locate target objects. Recent advances in semantic navigation have demonstrated op…
TartanGround: A Large-Scale Dataset for Ground Robot Perception and Navigation
Manthan Patel, Fan Yang, Yuheng Qiu +4
We present TartanGround, a large-scale, multi-modal dataset to advance the perception and autonomy of ground robots operating in diverse environments. This dataset, collected in va…
RayFronts: Open-Set Semantic Ray Frontiers for Online Scene Understanding and Exploration
Omar Alama, Avigyan Bhattacharya, Haoyang He +6
Open-set semantic mapping is crucial for open-world robots. Current mapping approaches either are limited by the depth range or only map beyond-range entities in constrained settin…
MAC-VO: Metrics-aware Covariance for Learning-based Stereo Visual Odometry
Yuheng Qiu, Yutian Chen, Zihao Zhang +2
We propose the MAC-VO, a novel learning-based stereo VO that leverages the learned metrics-aware matching uncertainty for dual purposes: selecting keypoint and weighing the residua…