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Huaping Liu

6 papers hereh-index 381 citations6 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • last author6

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cs.RO4
  • cs.AI1
  • cs.CV1
same name
  • Huaping Liu — 34 papers, h 48
  • Huaping Liu — 9 papers, h 3
  • Huaping Liu — 7 papers, h 4
  • Huaping Liu — 6 papers, h 5
  • Huaping Liu — 6 papers, h 4
  • Huaping Liu — 6 papers, h 5

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
most citedStimulate the Potential of Robots via Competition

6 citations · 12 across the 6 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.RO2024

Learning a Distributed Hierarchical Locomotion Controller for Embodied Cooperation

Chuye Hong, Kangyao Huang, Huaping Liu

In this work, we propose a distributed hierarchical locomotion control strategy for whole-body cooperation and demonstrate the potential for migration into large numbers of agents.…

cs.AI2024★ 4 cited

CompetEvo: Towards Morphological Evolution from Competition

Kangyao Huang, Di Guo, Xinyu Zhang +2

Training an agent to adapt to specific tasks through co-optimization of morphology and control has widely attracted attention. However, whether there exists an optimal configuratio…

cs.RO2024★ 6 cited

Stimulate the Potential of Robots via Competition

Kangyao Huang, Di Guo, Xinyu Zhang +2

It is common for us to feel pressure in a competition environment, which arises from the desire to obtain success comparing with other individuals or opponents. Although we might g…

cs.CV2024★ 2 cited

Efficient Multi-scale Network with Learnable Discrete Wavelet Transform for Blind Motion Deblurring

Xin Gao, Tianheng Qiu, Xinyu Zhang +6

Coarse-to-fine schemes are widely used in traditional single-image motion deblur; however, in the context of deep learning, existing multi-scale algorithms not only require the use…

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