My name is Yiming Li. I am currently a second year PhD student in the Robot Learning & Interaction group at the Idiap Research Institute and École Polytechnique Fédérale de Lausanne (EPFL), supervised by Dr. Sylvain Calinon.

I am broadly interested in planning, manipulation, and learning for robotic systems that interact with their surroundings and humans. Currently, my focus is on differentiable representations in manipulation planning tasks.

Why differentiable representations? Gradients play a crucial role in AI’s training and optimization processes. Gradient-based optimization techniques are widely used in learning, planning, and control. However, these components are usually computed separately (for instance, learning and planning typically focus on the task space, while control commands are in the joint space). On the other hand, end-to-end approaches directly output control commands but function as a black box. Differentiable robot representation bridges these approaches, allowing for gradient-based optimization from high-level scene understanding to low-level control in a unified framework. Differential geometries and equations are also appealing in solving robot manipulation problems. They are well-studied in mathematics but usually hard to scale to high-dimensional robot systems. Neural PDE/ODE solvers seem promising.

During my master’s, I worked on learning-based approaches for robotic grasping in cluttered environments.

I welcome the opportunity to listen to others and exchange ideas. Please feel free to drop me an email if you want to discuss anything with me!

🔥 News

📝 Selected Publications

Please visit my Google Scholar page for full publications.

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Configuration Space Distance Fields for Manipulation Planning

Yiming Li, Xuemin Chi, Amirreza Razmjoo, Sylvain Calinon

In Proc. Robotics: Science and Systems 2024 (RSS 2024).

Best Paper Award Finalist

[paper][website]

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Online Learning of Continuous Signed Distance Fields Using Piecewise Polynomials

Ante Marić, Yiming Li, Sylvain Calinon

IEEE Robotics and Automation Letters (RA-L), 9 (6), 6020-6026.

[paper][website]

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Representing Robot Geometry as Distance Fields: Applications to Whole-body Manipulation

Yiming Li, Yan Zhang, Amirreza Razmjoo, Sylvain Calinon

In Proc. IEEE Intl Conf. on Robotics and Automation 2024 (ICRA 2024).

[paper][website]

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HGC-Net: Deep Anthropomorphic Hand Grasping in Clutter

Yiming Li, Wei Wei, Daheng Li, Peng Wang, Wanyi Li, Jun Zhong

In Proc. IEEE Intl Conf. on Robotics and Automation 2022 (ICRA 2022).

[paper]

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Learning Human-to-robot Dexterous Handovers for Anthropomorphic Hand

Hoanan Duan, Peng Wang, Yiming Li, Daheng Li, Wei Wei

IEEE Transactions on Cognitive and Developmental Systems(T-CDS) 15 (3), 1224-1238.

[paper]

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DVGG: Deep Variational Grasp Generation for Dextrous Manipulation

Wei Wei, Daheng Li, Peng Wang, Yiming Li, Wanyi Li,Yongkang Luo, Jun Zhong

IEEE Robotics and Automation Letters (RA-L) 7 (2), 1659-1666.

[paper]

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Simultaneous Semantic and Collision Learning for 6-dof Grasp Pose Estimation

Yiming Li, Tao Kong, Ruihang Chu, Yifeng Li, Peng Wang, Lei Li

In Proc. IEEE/RSJ Intl Conf. on Intelligent Robots and Systems 2022 (IROS 2022).

[paper]

📖 Educations

  • 2022.10 - now, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
  • 2019.06 - 2022.06, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
  • 2015.09 - 2019.06, Tongji University, Shanghai, China.

📞 Contact

  • Email: ymli.cn@gmail.com
  • Telephone: (+41) 77 278 38 48
  • Address: Idiap Research Institute, Centre du Parc, Rue Marconi 19, CH-1920 Martigny, Switzerland