26 citations · 78 across the 11 of their papers we have counts for
11 papers
3D Hierarchical Refinement and Augmentation for Unsupervised Learning of Depth and Pose from Monocular Video
Guangming Wang, Jiquan Zhong, Shijie Zhao +3
Depth and ego-motion estimations are essential for the localization and navigation of autonomous robots and autonomous driving. Recent studies make it possible to learn the per-pix…
Efficient 3D Deep LiDAR Odometry
Guangming Wang, Xinrui Wu, Shuyang Jiang +2
An efficient 3D point cloud learning architecture, named EfficientLO-Net, for LiDAR odometry is first proposed in this paper. In this architecture, the projection-aware representat…
Motion Projection Consistency Based 3D Human Pose Estimation with Virtual Bones from Monocular Videos
Guangming Wang, Honghao Zeng, Ziliang Wang +2
Real-time 3D human pose estimation is crucial for human-computer interaction. It is cheap and practical to estimate 3D human pose only from monocular video. However, recent bone sp…
End-to-End 3D Point Cloud Learning for Registration Task Using Virtual Correspondences
Zhijian Qiao, Huanshu Wei, Zhe Liu +2
3D Point cloud registration is still a very challenging topic due to the difficulty in finding the rigid transformation between two point clouds with partial correspondences, and i…
Learning of Long-Horizon Sparse-Reward Robotic Manipulator Tasks with Base Controllers
Guangming Wang, Minjian Xin, Wenhua Wu +2
Deep Reinforcement Learning (DRL) enables robots to perform some intelligent tasks end-to-end. However, there are still many challenges for long-horizon sparse-reward robotic manip…
Mobile Robot Path Planning in Dynamic Environments through Globally Guided Reinforcement Learning
Binyu Wang, Zhe Liu, Qingbiao Li +1
Path planning for mobile robots in large dynamic environments is a challenging problem, as the robots are required to efficiently reach their given goals while simultaneously avoid…
Modelling and Dynamic Tracking Control of Industrial Vehicles with Tractor-trailer Structure
Hongchao Zhao, Zhe Liu, Zhiqiang Li +4
Existing works on control of tractor-trailers systems only consider the kinematics model without taking dynamics into account. Also, most of them treat the issue as a pure control…
Retrieval-based Localization Based on Domain-invariant Feature Learning under Changing Environments
Hanjiang Hu, Hesheng Wang, Zhe Liu +3
Visual localization is a crucial problem in mobile robotics and autonomous driving. One solution is to retrieve images with known pose from a database for the localization of query…
Coordinating Large-Scale Robot Networks with Motion and Communication Uncertainties for Logistics Applications
Zhe Liu, Hesheng Wang, Shunbo Zhou +2
In this paper, we focus on the problem of task allocation, cooperative path planning and motion coordination of the large-scale system with thousands of robots, aiming for practica…
SeqLPD: Sequence Matching Enhanced Loop-Closure Detection Based on Large-Scale Point Cloud Description for Self-Driving Vehicles
Zhe Liu, Chuanzhe Suo, Shunbo Zhou +4
Place recognition and loop-closure detection are main challenges in the localization, mapping and navigation tasks of self-driving vehicles. In this paper, we solve the loop-closur…
LPD-Net: 3D Point Cloud Learning for Large-Scale Place Recognition and Environment Analysis
Zhe Liu, Shunbo Zhou, Chuanzhe Suo +4
Point cloud based place recognition is still an open issue due to the difficulty in extracting local features from the raw 3D point cloud and generating the global descriptor, and…