Summary

Surgical robots have transformed operating rooms and reshaped many surgical procedures over the past decades, and their impact will continue to grow. The da Vinci Surgical System (dVSS) is widely regarded as one of the most representative platforms in this field. However, access to dVSS hardware is largely limited to a small number of well-resourced institutions, creating significant barriers for researchers seeking to contribute to robot-assisted minimally invasive surgery (RAMIS). This competition aims to bridge the gap between general-purpose robotic platforms and specialized surgical systems such as the dVSS. Participating teams will address laparoscopic manipulation challenges using accessible, general-purpose robotic arms, thereby helping to democratize research in surgical robotics and teleoperation. Team registration is open here.

Summary

Robot-assisted minimally invasive surgery relies heavily on endoscopic vision, yet the surgical scene visible to the camera represents only a limited portion of the surrounding anatomy. During robotic manipulation, tissue deformation can propagate beyond the current field of view, making potentially important shape changes difficult to observe and predict. This challenge aims to advance predictive perception for robotic surgery by encouraging participants to estimate hidden tissue geometry and deformation from multimodal information, including endoscopic observations, depth data, camera calibration, robotic kinematics, and 3D organ models. Participating teams will address two tasks: out-of-field scene depth and flow extrapolation, and out-of-field 3D deformation estimation of manipulated organs. By providing a focused benchmark for robot-induced deformation prediction in endoscopic operations, RoDEO aims to support the development of safer and more context-aware robotic surgical systems. Team registration and dataset access are available here.