https://github.com/JanMatas/Rainbow_ddpg
공식 코드Sim-to-Real Reinforcement Learning for Deformable Object Manipulation
Papers with Code 아카이브
Deformable Object Manipulation
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/WanquanF/RMA-Net
공식 코드Recurrent Multi-view Alignment Network for Unsupervised Surface Registration
https://github.com/Xingyu-Lin/VCD
공식 코드https://github.com/Xingyu-Lin/softgym
공식 코드SoftGym: Benchmarking Deep Reinforcement Learning for Deformable Object Manipulation
https://github.com/dikay1/os-agdo
공식 코드One-Shot Affordance Grounding of Deformable Objects in Egocentric Organizing Scenes
https://github.com/ericcsr/diffsrl
공식 코드https://github.com/sail-sg/ild
공식 코드https://github.com/shamilmamedov/flexible_arm
공식 코드Safe Imitation Learning of Nonlinear Model Predictive Control for Flexible Robots
https://github.com/uscresl/dmfd
공식 코드Learning Deformable Object Manipulation from Expert Demonstrations
https://github.com/wilson1yan/rlpyt
공식 코드Learning to Manipulate Deformable Objects without Demonstrations
https://github.com/xiaoxiaoxh/DeformPAM
공식 코드https://github.com/DanielTakeshi/IL_ROS_HSR
Deep Transfer Learning of Pick Points on Fabric for Robot Bed-Making
https://github.com/DanielTakeshi/fast_grasp_detect
Deep Transfer Learning of Pick Points on Fabric for Robot Bed-Making
https://github.com/Jianghanxiao/PhysTwin
PhysTwin: Physics-Informed Reconstruction and Simulation of Deformable Objects from Videos
https://github.com/skylark0924/rofunc
Robot Cooking with Stir-fry: Bimanual Non-prehensile Manipulation of Semi-fluid Objects
https://github.com/sparkmxy/my-offlinerl
PLAS: Latent Action Space for Offline Reinforcement Learning
https://github.com/takuseno/d3rlpy
PLAS: Latent Action Space for Offline Reinforcement Learning
https://github.com/wilson1yan/contrastive-forward-model
Learning Predictive Representations for Deformable Objects Using Contrastive Estimation
https://github.com/xingyu-lin/softagent
Learning to Manipulate Deformable Objects without Demonstrations
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.