Event
Bimanual surgical robot performs appendectomy in live rabbits without robot demonstrations
1 reports · 1 sources
The research team led by Dongho Yee proposed an end-to-end training pipeline: using instrument state loggers mounted on standard laparoscopic instrument shafts (containing inertial, time-of-flight, and Hall sensors, requiring no external cameras or trackers) to collect instrument pose and jaw state during surgeons' operations, training a bimanual surgical robot policy, and validating it on live animals. The policy was first retrained with 849 demonstrations from 4 live rabbits, then deployed on another 4 live rabbits equipped with electrosurgical devices; the surgeon selected the surgical phase, and the policy completed appendectomy on 3 of these animals. Both demonstration datasets have been made public.
Report timeline
- Learning Bimanual Laparoscopic Appendectomy Without Robot-Collected Demonstrations, Validated on Live Animals
The paper proposes an end-to-end pipeline that uses an instrument-state logger mounted on the shaft of a standard laparoscopic instrument (combining inertial, time-of-flight, and Hall sensors, with no external camera or tracker) to capture the instrument pose and jaw state during a surgeon's operation, which is then used to train a surgical robot policy and validated on live animals.
arXiv cs.RO ·