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Contact-rich Manipulation

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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/baceituno/dlm

공식 코드

A Differentiable Recipe for Learning Visual Non-Prehensile Planar Manipulation

https://github.com/cambel/robot-learning-cl-dr

공식 코드

Accelerating Robot Learning of Contact-Rich Manipulations: A Curriculum Learning Study

https://github.com/haoyizhu/pointcloudmatters

공식 코드

Point Cloud Matters: Rethinking the Impact of Different Observation Spaces on Robot Learning

https://github.com/haoyizhu/realrobot

공식 코드

Point Cloud Matters: Rethinking the Impact of Different Observation Spaces on Robot Learning

https://github.com/omron-sinicx/compact

공식 코드

Learning Variable Compliance Control From a Few Demonstrations for Bimanual Robot with Haptic Feedback Teleoperation System

https://github.com/stanford-iprl-lab/multimodal_representation

공식 코드

Making Sense of Vision and Touch: Self-Supervised Learning of Multimodal Representations for Contact-Rich Tasks

https://github.com/xiaoxiaoxh/reactive_diffusion_policy

공식 코드

Reactive Diffusion Policy: Slow-Fast Visual-Tactile Policy Learning for Contact-Rich Manipulation

https://github.com/Henry1iu/ierg5350_rl_course_project

Making Sense of Vision and Touch: Self-Supervised Learning of Multimodal Representations for Contact-Rich Tasks

https://github.com/abalakrishna123/recovery-rl

Recovery RL: Safe Reinforcement Learning with Learned Recovery Zones

https://github.com/zlr20/saferl_kit

Recovery RL: Safe Reinforcement Learning with Learned Recovery Zones

https://github.com/zuoxingdong/VIN_PyTorch_Visdom

Learning from the Hindsight Plan -- Episodic MPC Improvement

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.