Researchers at the University of California Berkeley have successfully demonstrated autonomous debridement capabilities with their RAVEN robot. This is the first example of a fully autonomous subtask implemented on the RAVEN. In a simplified scenario, the robot is able to detect the locations of dead tissue and remove it to a safe location.

Graduate students, under the supervision of Professors Ken Goldberg and Pieter Abbeel, were able to take advantage of the open source RAVEN architecture in order to integrate stereo camera hardware and  Model Predictive Control software. Together, these systems are used to enable a vision-guided, autonomous application for the the robot. One day, this contribution can be used to enable surgery in remote locations where a surgeon may only have limited control of the robot due to communication limitations. A paper detailing the methods has been submitted to the IEEE for publication in 2014. This work indicates a major contribution to the field of robotic surgery and machine learning from a RAVEN team.

The advancements from the Berkeley team are shared with the RAVEN community by providing other users with their code. Several teams are actively working on adapting this software for their own research goals.

Find more information at the team’s RAVEN site.