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Ruohan Zhang

4 papers here

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

author position
  • first author1
  • middle author2
  • last author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.RO4
ORCID 0000-0001-6681-3360
same name
  • Ruohan Zhang — 7 papers, h 16
  • Ruohan Zhang — 1 paper
  • Ruohan Zhang — 1 paper
  • Ruohan Zhang — 1 paper

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

most citedNOIR: Neural Signal Operated Intelligent Robots for Everyday Activities

8 citations · 16 across the 4 of their papers we have counts for

collaborators

4 papers

cs.RO2024★ 1 cited

TeleMoMa: A Modular and Versatile Teleoperation System for Mobile Manipulation

Shivin Dass, Wensi Ai, Yuqian Jiang +6

A critical bottleneck limiting imitation learning in robotics is the lack of data. This problem is more severe in mobile manipulation, where collecting demonstrations is harder tha…

cs.RO2024★ 6 cited

BEHAVIOR-1K: A Human-Centered, Embodied AI Benchmark with 1,000 Everyday Activities and Realistic Simulation

Chengshu Li, Ruohan Zhang, Josiah Wong +32

We present BEHAVIOR-1K, a comprehensive simulation benchmark for human-centered robotics. BEHAVIOR-1K includes two components, guided and motivated by the results of an extensive s…

cs.RO2023★ 8 cited

NOIR: Neural Signal Operated Intelligent Robots for Everyday Activities

Ruohan Zhang, Sharon Lee, Minjune Hwang +11

We present Neural Signal Operated Intelligent Robots (NOIR), a general-purpose, intelligent brain-robot interface system that enables humans to command robots to perform everyday a…

cs.RO2023★ 1 cited

Primitive Skill-based Robot Learning from Human Evaluative Feedback

Ayano Hiranaka, Minjune Hwang, Sharon Lee +4

Reinforcement learning (RL) algorithms face significant challenges when dealing with long-horizon robot manipulation tasks in real-world environments due to sample inefficiency and…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.