Cognitive Robotic Architecture for Semi-Autonomous Execution of Manipulation Tasks in a Surgical Environment

Abstract

The development of robotic systems with a certain level of autonomy to be used in critical scenarios, such as an operating room, necessarily requires a seamless integration of multiple state-of-the-art technologies. In this paper we propose a cognitive robotic architecture that is able to help an operator accomplish a specific task. The architecture integrates an action recognition module to understand the scene, a supervisory control to make decisions, and a model predictive control to plan collision-free trajectory for the robotic arm taking into account obstacles and model uncertainty. The proposed approach has been validated on a simplified scenario involving only a da VinciO surgical robot and a novel manipulator holding standard laparoscopic tools.