Resources

Some good resources and papers to take a look if you are applying for PhD, Research Assistant or Research Intern positions:

具身智能技术指南 Embodied-AI-Guide

How to Get Started with Embodied AI Research

ICRA 2026 Workshop | Dexterity with Multifingered Hands:Hardware, Sensing, and Skills

CoRL 2025 Livestream

RSS 2025 Livestream

Lumina具身智能社区

Sharpa GTC 2026 Presentation - Unlocking High-DoF Dexterity via Tactile AI

灵巧手、数据、触觉：为什么大家都在聊 Sharpa？

Robot Learning

1. Luo, J., Xu, C., Wu, J., & Levine, S. (2025). Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning. Science Robotics. 10, eads5033. DOI:10.1126/scirobotics.ads5033

2. Lei, K., Li, H., Yu, D., Wei, Z., Guo, L., Jiang, Z., ... & Xu, H. (2025). RL-100: Performant Robotic Manipulation with Real-World Reinforcement Learning. arXiv preprint arXiv:2510.14830. (Science Robotics)

3. Yu, D., Lei, K., Jiang, Z., Pan, J., & Xu, H. (2026). Beyond Action Residuals: Real-World Robot Policy Steering via Bottleneck Latent Reinforcement Learning. arXiv preprint arXiv:2605.19919. (Latent steering RL)

4. Li, H., Lei, K., Zang, S., Hu, K., Liang, Y., An, B., ... & Xu, H. (2026). Failure-Aware RL: Reliable Offline-to-Online Reinforcement Learning with Self-Recovery for Real-World Manipulation. arXiv preprint arXiv:2601.07821.

5. Yang, J., Lin, K., Li, J., Zhang, W., Lin, T., Wu, L., ... & Li, H. (2026). Rise: Self-improving robot policy with compositional world model. arXiv preprint arXiv:2602.11075. (RSS 2026)

6. Wang, Y., Li, X., Xie, P., Yang, P., Nie, B., Cai, Y., ... & Luo, J. (2026). Learning while Deploying: Fleet-Scale Reinforcement Learning for Generalist Robot Policies. arXiv preprint arXiv:2605.00416.

7. Hou, Y., Liu, Z., Chi, C., Cousineau, E., Kuppuswamy, N., Feng, S., ... & Song, S. (2024). Adaptive Compliance Policy: Learning Approximate Compliance for Diffusion Guided Control. arXiv preprint arXiv:2410.09309.

8. Choi, H., Hou, Y., Pan, C., Hong, S., Patel, A., Xu, X., ... & Song, S. (2026). In-the-Wild Compliant Manipulation with UMI-FT. arXiv preprint arXiv:2601.09988.

9. Zhang, H., Huang, W. H., Tong, Q., Solak, G., Liu, P., Liu, S., ... & Ajoudani, A. (2026). CompliantVLA-adaptor: VLM-Guided Variable Impedance Action for Safe Contact-Rich Manipulation. arXiv preprint arXiv:2601.15541.

10. Xue, H., Ren, J., Chen, W., Zhang, G., Fang, Y., Gu, G., ... & Lu, C. (2025). Reactive Diffusion Policy: Slow-Fast Visual-Tactile Policy Learning for Contact-Rich Manipulation. arXiv preprint arXiv:2503.02881.

11. Chen, W., Xue, H., Wang, Y., Zhou, F., Lv, J., Jin, Y., ... & Lu, C. (2025). ImplicitRDP: An End-to-End Visual-Force Diffusion Policy with Structural Slow-Fast Learning. arXiv preprint arXiv:2512.10946.

12. Fang, H., Tang, S., Mei, M., Qin, H., He, Z., Chen, J., ... & Wang, S. (2026). Force Policy: Learning Hybrid Force-Position Control Policy under Interaction Frame for Contact-Rich Manipulation. arXiv preprint arXiv:2602.22088.

13. Yu, J., Liu, H., Yu, Q., Ren, J., Hao, C., Ding, H., ... & Zhang, W. (2025). ForceVLA: Enhancing VLA Models with a Force-aware MoE for Contact-rich Manipulation. arXiv preprint arXiv:2505.22159.

14. Yang, Y., Chen, A., Zhu, Z., Xu, K., Mao, Y., Wei, Y., ... & Wang, Y. (2026). Direction Matters: Learning Force Direction Enables Sim-to-Real Contact-Rich Manipulation. arXiv preprint arXiv:2602.14174.

15. Zhu, X., Huang, B., & Li, Y. (2025). Touch in the Wild: Learning Fine-Grained Manipulation with a Portable Visuo-Tactile Gripper. arXiv preprint arXiv:2507.15062., NeurIPS 2025.

16. Huang, B., Xu, J., Akinola, I., Yang, W., Sundaralingam, B., O'Flaherty, R., ... & Li, Y. (2025). VT-Refine: Learning Bimanual Assembly with Visuo-Tactile Feedback via Simulation Fine-Tuning, CoRL 2025.

17. Zhang, Z., Xu, H., Yang, Z., Yue, C., Lin, Z., Gao, H. A., ... & Zhao, H. (2025). TA-VLA: Elucidating the Design Space of Torque-aware Vision-Language-Action Models. arXiv preprint arXiv:2509.07962, CoRL 2025.

18. Huang, D., Navab, N., & Jiang, Z. (2025). Improving Robustness to Out-of-Distribution States in Imitation Learning via Deep Koopman-Boosted Diffusion Policy. IEEE Transactions on Robotics.

19. Gong, Z., Lyu, S., Ding, P., Xiao, W., & Wang, D. (2025). Robust Online Residual Refinement via Koopman-Guided Dynamics Modeling. arXiv preprint arXiv:2509.12562.

20. Ruan, M., Zhou, L., Li, H., Wang, Z., Lu, Z., Zhang, J., & Fang, B. (2026). ReTac-ACT: A State-Gated Vision-Tactile Fusion Transformer for Precision Assembly. arXiv preprint arXiv:2603.09565. (Manipulation Net Evaluation)

21. Zhang, Z., Ma, J., Yang, X., Wen, X., Zhang, Y., Li, B., ... & Ma, D. (2026). TouchGuide: Inference-Time Steering of Visuomotor Policies via Touch Guidance. arXiv preprint arXiv:2601.20239. (RSS 2026)

22. Zheng, Y., Gu, S., Li, W., Zheng, Y., Zang, Y., Tian, S., ... & Ding, W. (2026). OmniVTA: Visuo-Tactile World Modeling for Contact-Rich Robotic Manipulation. arXiv preprint arXiv:2603.19201.

23. Yuan, H., Yi, W., Zhang, Z., Chen, W., Mo, Y., Yin, J., ... & Lourentzou, I. (2026). Vtam: Video-tactile-action models for complex physical interaction beyond vlas. arXiv preprint arXiv:2603.23481. 

24. Bronars, A., Park, Y., & Agrawal, P. (2026). Tune to Learn: How Controller Gains Shape Robot Policy Learning. arXiv preprint arXiv:2604.02523, RSS 2026 (connecting controller tuning, compliance control and robot learning)

25. Zang, Y., Zheng, Y., Nie, X., Zheng, Y., Tian, S., Gu, S., ... & Ding, W. (2026). TacForeSight: Force-Guided Tactile World Model for Contact-Rich Manipulation. arXiv preprint arXiv:2606.11184. (Tactile World Model)

Dexterous Hand Manipulation 

26. Heng, L., Geng, H., Zhang, K., Abbeel, P., & Malik, J. (2025). ViTacFormer: Learning Cross-Modal Representation for Visuo-Tactile Dexterous Manipulation. arXiv preprint arXiv:2506.15953. (RSS 2026)

27. Qi, H., Kumar, A., Calandra, R., Ma, Y., & Malik, J. (2023). In-hand object rotation via rapid motor adaptation. In Conference on Robot Learning (pp. 1722-1732). PMLR.

28. Yin, Z. H., Huang, B., Qin, Y., Chen, Q., & Wang, X. (2023). Rotating without seeing: Towards in-hand dexterity through touch. arXiv preprint arXiv:2303.10880, RSS 2023.

29. Hsieh, E., Hsieh, W. H., Wang, Y. J., Lin, T., Malik, J., Sreenath, K., & Qi, H. (2025). Learning Dexterous Manipulation Skills from Imperfect Simulations. arXiv preprint arXiv:2512.02011.

30. Liu, X., Wang, H., & Yi, L. (2025). DexNDM: Closing the Reality Gap for Dexterous In-Hand Rotation via Joint-Wise Neural Dynamics Model. arXiv preprint arXiv:2510.08556.

31. Su, L., Peng, Z., Ren, R., Mao, S., Du, J., Zhang, K., & Zhu, X. (2026). Tacmap: Bridging the tactile sim-to-real gap via geometry-consistent penetration depth map. arXiv preprint arXiv:2602.21625.

32. Huang, J., Ye, Y., Gong, Y., Zhu, X., Gao, Y., & Zhang, K. (2025). Spatially anchored Tactile Awareness for Robust Dexterous Manipulation. arXiv preprint arXiv:2510.14647.

33. Chen, C., Yu, Z., Choi, H., Cutkosky, M., & Bohg, J. (2025). Dexforce: Extracting force-informed actions from kinesthetic demonstrations for dexterous manipulation. IEEE Robotics and Automation Letters. (Similar to ACP, dexterous hand version)

34. Suresh, S., Qi, H., Wu, T., Fan, T., Pineda, L., Lambeta, M., ... & Mukadam, M. (2024). NeuralFeels with neural fields: Visuotactile perception for in-hand manipulation. Science Robotics, 9(96), eadl0628.

35. Ye, Q., Liu, Q., Wang, S., Chen, J., Cui, Y., Jin, K., ... & Chen, J. (2026). Visual-tactile pretraining and online multitask learning for humanlike manipulation dexterity. Science Robotics, 11(110), eady2869.

36. Tang, T., Ji, X., Xing, W., Hao, C., Xu, W., Shao, L., ... & Zhang, K. (2026). Towards Human-Like Manipulation through RL-Augmented Teleoperation and Mixture-of-Dexterous-Experts VLA. arXiv preprint arXiv:2603.08122.

37. Han, Y., Chen, Z., Zhao, Y., Xu, C., Shao, Y., Peng, Y., ... & Lian, W. (2026). DexHiL: A Human-in-the-Loop Framework for Vision-Language-Action Model Post-Training in Dexterous Manipulation. arXiv preprint arXiv:2603.09121.

38. Zhang, C., Cai, P., Yuan, H., Xu, C., & Lu, Z. (2025). UniTacHand: Unified Spatio-Tactile Representation for Human to Robotic Hand Skill Transfer. arXiv preprint arXiv:2512.21233.

39. Xu, Z., Wang, Y., Abbatematteo, B., Preechayasomboon, J., Chan, S., Colonnese, N., & Memar, A. H. (2026). Contact-Grounded Policy: Dexterous Visuotactile Policy with Generative Contact Grounding. arXiv preprint arXiv:2603.05687. (Tactile compliance policy, RSS 2026)

40. Li, Z., Huang, L., Xu, W., Zhu, Z., Lin, N., Ma, X., ... & Wen, R. (2026). Hand-in-the-Loop: Improving Dexterous VLA via Seamless Interventional Correction. arXiv preprint arXiv:2605.15157. (Relative Hand Retargeting)

41. Atar, S., Huang, Y. T., & Yip, M. (2026). Transferring Contact, Not Just Motion: Compliant Grasping Across Dexterous Hands. arXiv preprint arXiv:2606.15516. (Contact-aware Retargeting)

42. Wu, J., Yao, S., He, G., Liu, X., Zeng, Z., Jiang, X., ... & Zhao, H. (2026). TopoRetarget: Interaction-Preserving Retargeting for Dexterous Manipulation. arXiv preprint arXiv:2606.16272. (Hand-object Retargeting)

43. Guo, C., Chen, X., Zeng, Z., Guo, Z., Li, Y., Xiao, H., ... & Lu, H. (2025). Grasp like humans: Learning generalizable multi-fingered grasping from human proprioceptive sensorimotor integration. IEEE Transactions on Robotics.

44. Niu, D., Liu, Z., Wang, Z., Shao, B., Yin, Z. H., Pai, A., ... & Darrell, T. (2026). T-Rex: Tactile-Reactive Dexterous Manipulation. arXiv preprint arXiv:2606.17055.

45. Yuan, C., Zhang, Z., Zhou, M., Chen, W., Wang, Y., Liu, Z., ... & Gao, Y. (2026). FTP-1: A Generalist Foundation Tactile Policy Across Tactile Sensors for Contact-Rich Manipulation. arXiv preprint arXiv:2606.13102.

46. Zhu, X., Liu, Z., Jain, S., Li, C., Noori, M., Zhao, H., ... & Chang, Y. (2026). Learning Dexterous Manipulation Using Contact Wrench Guidance From Human Demonstration. arXiv preprint arXiv:2607.00033. (object-centric | wrench guidance)

Robot Compliance Control

47. Shi, H., Hu, S., Hou, Y., Wang, W., Liu, K., & Shuran Song. (2026). Minimalist Compliance Control. arXiv preprint arXiv:2603.00913.

48. Haddadin, S., & Shahriari, E. (2024). Unified force-impedance control. The International Journal of Robotics Research, 43(13), 2112-2141.

49. Li, Y., Zheng, L., Wang, Y., Dong, E., & Zhang, S. (2025). Impedance Learning-based Adaptive Force Tracking for Robot on Unknown Terrains. IEEE Transactions on Robotics.

50. Hou, Y., Liu, Z., Chi, C., Cousineau, E., Kuppuswamy, N., Feng, S., ... & Song, S. (2024). Adaptive Compliance Policy: Learning Approximate Compliance for Diffusion Guided Control. arXiv preprint arXiv:2410.09309.

51. Zhi, P., Li, P., Yin, J., Jia, B., & Huang, S. (2025). Learning Unified Force and Position Control for Legged Loco-Manipulation. arXiv preprint arXiv:2505.20829, CoRL 2025 Best Paper Award.

52. Geiger, N., Asfour, T., Hogan, N., & Lachner, J. (2025). Diffusion-Based Impedance Learning for Contact-Rich Manipulation Tasks. arXiv preprint arXiv:2509.19696.

Aerial Manipulation

53. He, G., Guo, X., Tang, L., Zhang, Y., Mousaei, M., Xu, J., ... & Shi, G. (2025). Flying Hand: End-Effector-Centric Framework for Versatile Aerial Manipulation Teleoperation and Policy Learning. arXiv preprint arXiv:2504.10334.

54. Gupta, H., Guo, X., Ha, H., Pan, C., Cao, M., Lee, D., ... & Shi, G. (2025). UMI-on-Air: Embodiment-Aware Guidance for Embodiment-Agnostic Visuomotor Policies. arXiv preprint arXiv:2510.02614.

55. Sun, S., Wang, X., Sanalitro, D., Franchi, A., Tognon, M., & Alonso-Mora, J. (2025). Agile and Cooperative Aerial Manipulation of a Cable-Suspended Load. arXiv preprint arXiv:2501.18802. Science Robotics.

56. Duan, Y., Li, H., Wu, Y., Yu, W., Zhang, X., Shen, Y., ... & Zhang, Y. (2025). STDArm: Transferring Visuomotor Policies From Static Data Training to Dynamic Robot Manipulation. arXiv preprint arXiv:2504.18792, RSS 2025