Physical Grounding of LLM (SayTap, RoboCat, Language to Rewards for Robotic Skill Synthesis)
구글 딥마인드의 LLM활용 로보틱스 논문이 한번에 여러개 나와,
네이버 클라우드 하정우 박사님께서 운영하시는 Weekly AI ArXiv에서 정말 가볍게 소개.
https://github.com/jungwoo-ha/WeeklyArxivTalk/issues/87#issuecomment-1606018653
[20230625] Weekly AI ArXiv 만담 시즌2 - 21회차 · Issue #87 · jungwoo-ha/WeeklyArxivTalk
Zoom webinar: https://navercorp.zoom.us/j/92208940283 News 6.25 73주년 순국선열들의 희생에 감사드립니다. Conferences EMNLP 2023 deadline: 모두 수고하셨습니다. CVPR 2023: 모두들 의미있는 학회 보내셨나요~ Best Paper: V
github.com
SayTap: Language to Quadrupedal Locomotion
Use foot contact pattern to bridge LLM and low-level controller.
saytap.github.io
RoboCat: A self-improving robotic agent
Robots are quickly becoming part of our everyday lives, but they’re often only programmed to perform specific tasks well. While harnessing recent advances in AI could lead to robots that could help in many more ways, progress in building general-purpose
www.deepmind.com
https://language-to-reward.github.io/
Language to Reward for Robotic Skill Synthesis
Project page for Language to Reward for Robotic Skill Synthesis.
language-to-reward.github.io