107 citations · 465 across the 85 of their papers we have counts for
18 papers · 1 filter
Open-Set Object Detection Using Classification-free Object Proposal and Instance-level Contrastive Learning
Zhongxiang Zhou, Yifei Yang, Yue Wang +1
Detecting both known and unknown objects is a fundamental skill for robot manipulation in unstructured environments. Open-set object detection (OSOD) is a promising direction to ha…
DeepRING: Learning Roto-translation Invariant Representation for LiDAR based Place Recognition
Sha Lu, Xuecheng Xu, Li Tang +2
LiDAR based place recognition is popular for loop closure detection and re-localization. In recent years, deep learning brings improvements to place recognition by learnable featur…
RING++: Roto-translation Invariant Gram for Global Localization on a Sparse Scan Map
Xuecheng Xu, Sha Lu, Jun Wu +5
Global localization plays a critical role in many robot applications. LiDAR-based global localization draws the community's focus with its robustness against illumination and seaso…
C^2:Co-design of Robots via Concurrent Networks Coupling Online and Offline Reinforcement Learning
Ci Chen, Pingyu Xiang, Haojian Lu +2
With the increasing computing power, using data-driven approaches to co-design a robot's morphology and controller has become a promising way. However, most existing data-driven me…
Efficient Distance-Optimal Tethered Path Planning in Planar Environments: The Workspace Convexity
Tong Yang, Rong Xiong, Yue Wang
The main contribution of this paper is the proof of the convexity of the omni-directional tethered robot workspace (namely, the set of all tether-length-admissible robot configurat…
Efficient Search of the k Shortest Non-Homotopic Paths by Eliminating Non-k-Optimal Topologies
Tong Yang, Li Huang, Yue Wang +1
An efficient algorithm to solve the shortest non-homotopic path planning (-SNPP) problem in a 2D environment is proposed in this paper. Motivated by accelerating the ineffic…
FEJ-VIRO: A Consistent First-Estimate Jacobian Visual-Inertial-Ranging Odometry
Shenhan Jia, Yanmei Jiao, Zhuqing Zhang +2
In recent years, Visual-Inertial Odometry (VIO) has achieved many significant progresses. However, VIO methods suffer from localization drift over long trajectories. In this paper,…
Towards Two-view 6D Object Pose Estimation: A Comparative Study on Fusion Strategy
Jun Wu, Lilu Liu, Yue Wang +1
Current RGB-based 6D object pose estimation methods have achieved noticeable performance on datasets and real world applications. However, predicting 6D pose from single 2D image f…
DPCN++: Differentiable Phase Correlation Network for Versatile Pose Registration
Zexi Chen, Yiyi Liao, Haozhe Du +5
Pose registration is critical in vision and robotics. This paper focuses on the challenging task of initialization-free pose registration up to 7DoF for homogeneous and heterogeneo…
Learning A Simulation-based Visual Policy for Real-world Peg In Unseen Holes
Liang Xie, Hongxiang Yu, Kechun Xu +5
This paper proposes a learning-based visual peg-in-hole that enables training with several shapes in simulation, and adapting to arbitrary unseen shapes in real world with minimal…
Map-based Visual-Inertial Localization: Consistency and Complexity
Zhuqing Zhang, Yanmei Jiao, Shoudong Huang +2
Drift-free localization is essential for autonomous vehicles. In this paper, we address the problem by proposing a filter-based framework, which integrates the visual-inertial odom…
Toward Consistent and Efficient Map-based Visual-inertial Localization: Theory Framework and Filter Design
Zhuqing Zhang, Yang Song, Shoudong Huang +2
This paper focuses on designing a consistent and efficient filter for map-based visual-inertial localization. First, we propose a new Lie group with its algebra, based on which a n…
Learning to Fill the Seam by Vision: Sub-millimeter Peg-in-hole on Unseen Shapes in Real World
Liang Xie, Hongxiang Yu, Yinghao Zhao +5
In the peg insertion task, human pays attention to the seam between the peg and the hole and tries to fill it continuously with visual feedback. By imitating the human behavior, we…
One RING to Rule Them All: Radon Sinogram for Place Recognition, Orientation and Translation Estimation
Sha Lu, Xuecheng Xu, Huan Yin +3
LiDAR-based global localization is a fundamental problem for mobile robots. It consists of two stages, place recognition and pose estimation, which yields the current orientation a…
DXQ-Net: Differentiable LiDAR-Camera Extrinsic Calibration Using Quality-aware Flow
Xin Jing, Xiaqing Ding, Rong Xiong +2
Accurate LiDAR-camera extrinsic calibration is a precondition for many multi-sensor systems in mobile robots. Most calibration methods rely on laborious manual operations and calib…
Translation Invariant Global Estimation of Heading Angle Using Sinogram of LiDAR Point Cloud
Xiaqing Ding, Xuecheng Xu, Sha Lu +6
Global point cloud registration is an essential module for localization, of which the main difficulty exists in estimating the rotation globally without initial value. With the aid…
A Visual Navigation Perspective for Category-Level Object Pose Estimation
Jiaxin Guo, Fangxun Zhong, Rong Xiong +3
This paper studies category-level object pose estimation based on a single monocular image. Recent advances in pose-aware generative models have paved the way for addressing this c…
Depth-Independent Depth Completion via Least Square Estimation
Xianze Fang, Yunkai Wang, Zexi Chen +2
The depth completion task aims to complete a per-pixel dense depth map from a sparse depth map. In this paper, we propose an efficient least square based depth-independent method t…