activity
20192021
most citedikd-Tree: An Incremental K-D Tree for Robotic Applications

69 citations · 155 across the 24 of their papers we have counts for

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6 papers · 1 filter

cs.RO20212 cited

MetaView: Few-shot Active Object Recognition

Wei Wei, Haonan Yu, Haichao Zhang +2

In robot sensing scenarios, instead of passively utilizing human captured views, an agent should be able to actively choose informative viewpoints of a 3D object as discriminative…

cs.RO2021

Avoiding dynamic small obstacles with onboard sensing and computating on aerial robots

Fanze Kong, Wei Xu, Fu Zhang

In practical applications, autonomous quadrotors are still facing significant challenges, such as the detection and avoidance of very small and even dynamic obstacles (e.g., tree b…

cs.RO20219 cited

R2LIVE: A Robust, Real-time, LiDAR-Inertial-Visual tightly-coupled state Estimator and mapping

Jiarong Lin, Chunran Zheng, Wei Xu +1

In this letter, we propose a robust, real-time tightly-coupled multi-sensor fusion framework, which fuses measurement from LiDAR, inertial sensor, and visual camera to achieve robu…

cs.RO202169 cited

ikd-Tree: An Incremental K-D Tree for Robotic Applications

Yixi Cai, Wei Xu, Fu Zhang

This paper proposes an efficient data structure, ikd-Tree, for dynamic space partition. The ikd-Tree incrementally updates a k-d tree with new coming points only, leading to much l…

cs.RO2020

Robots State Estimation and Observability Analysis Based on Statistical Motion Models

Wei Xu, Dongjiao He, Yixi Cai +1

This paper presents a generic motion model to capture mobile robots' dynamic behaviors (translation and rotation). The model is based on statistical models driven by white random p…

cs.RO2020

FAST-LIO: A Fast, Robust LiDAR-inertial Odometry Package by Tightly-Coupled Iterated Kalman Filter

Wei Xu, Fu Zhang

This paper presents a computationally efficient and robust LiDAR-inertial odometry framework. We fuse LiDAR feature points with IMU data using a tightly-coupled iterated extended K…