Jianwei Zhang
University of Hamburg
756 Papers
2.6K Citations
Jianwei Zhang is an academic researcher from University of Hamburg. The author has contributed to research in topics: Computer science & Robot. The author has an hindex of 39, co-authored 607 publications. Previous affiliations of Jianwei Zhang include Bielefeld University & Tsinghua University.
Chat about Author
Papers
Development of adaptive locomotion of a caterpillar-like robot based on a sensory feedback CPG model
TL;DR: A novel control mechanism for generating adaptive locomotion of a caterpillar-like robot in complex terrain by optimising the amount and speed of sensory input that is fed back to the CPG model.
Development of a practical power transmission line inspection robot based on a novel line walking mechanism
Ludan Wang,Fei Liu,Zhen Wang,Shaoqiang Xu,Sheng Cheng,Jianwei Zhang +5 more
- 03 Dec 2010
TL;DR: A mobile robot based on novel line-walking mechanism is proposed for inspecting power transmission lines to minimize the drive torque of the hip joint and keep the robot stable when only one leg is hung on line.
Semantic consistency learning on manifold for source data-free unsupervised domain adaptation
TL;DR: In this paper , a semantic consistency learning on manifold (SCLM) method was proposed for source data-free unsupervised domain adaptation (SFUDA), which generates pseudo-labels for target data using a new clustering method, EntMomClustering, that enhanced k-means clustering by fusing the entropy momentum.
28
High stiffness pneumatic actuating scheme and improved position control strategy realization of a pneumatic climbing robot
Houxiang Zhang,Wei Wang,Jianwei Zhang +2 more
- 22 Feb 2009
TL;DR: Experimental results prove that the two approaches can effectively improve the pneumatic actuating system's stiffness and control its quality.
28
ConsRec: Learning Consensus Behind Interactions for Group Recommendation
Xixi Wu,Yun Xiong,Yao Zhang,Yizhu Jiao,Jianwei Zhang,Yangyong Zhu,Philip S. Yu +6 more
- 07 Feb 2023
TL;DR: Wang et al. as mentioned in this paper designed a novel hypergraph neural network that allows for efficient hypergraph convolutional operations to generate expressive member-level aggregation, and an adaptive fusion component is further proposed to integrate and balance the multi-view information.