SutureFormer: Learning Surgical Trajectories via Goal-conditioned Offline RL in Pixel Space
Predicting surgical needle trajectories from endoscopic video is critical for robot-assisted suturing, enabling anticipatory planning, real-time guidance, and safer motion execution. Existing methods that directly learn motion distributions from visual observations tend to overlook the sequential dependency among adjacent motion steps. Moreover, sparse waypoint annotations often fail to provide sufficient supervision, further increasing the difficulty of supervised or imitation learning methods. To address these challenges, we formulate image-based needle trajectory prediction as a sequential decision-making problem, in which the needle tip is treated as an agent that moves step by step i...
| Authors | Huanrong Liu, Chunlin Tian, Tongyu Jia et al. |
|---|---|
| Primary category | cs.RO |
| Published | 19 March 2026 |
| Last updated at source | 5 July 2026 |
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