Autonomy is the next frontier of research in robotic surgery and its aim is to improve the quality of surgical procedures in the next future.

One fundamental requirement for autonomy is advanced perception capability through vision sensors.

In this article, we propose a novel calibration technique for a surgical scenario with a da Vinci® Research Kit (dVRK) robot. Camera and robotic arms calibration are necessary to precise position and emulate expert surgeons. The novel calibration technique is tailored for RGB-D cameras.

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The MULTIROBOTS-SURGERY platform is designed as a collection of functional modules, each one devoted to a single task.

We implemented the MULTIROBOTS-SURGERY platform as a collection of ROS* nodes. All the ROS nodes are connected to a central unit acting as ROS core, in charge of providing a common timestamp and driving the communication between nodes, and data recording module.

The figure shows the conceptual architecture of MULTIROBOTS-SURGERY platform in terms of ROS nodes.

*ROS is an open source, distributed, component-based development framework that has become the standard de facto for interfacing heterogeneous hardware and software in robotics applications.

To fulfil ethical and legal requirements SARAS project is aiming to reduce, refine and replace live animal experiments according to the 3Rs principle.

The robot motion planning is generally solved before the robot actually executes the desired motions and in case of motions that must avoid obstacles, this approach may work with static obstacles only. 

If, instead, obstacles are moving, the desired motion must be calculated in real-time, a few milliseconds before its execution.

SARAS Multirobots-Surgery is the first step toward the next generation of surgical robotic systems merging artificial intelligence, computer vision, machine learning and cognitive control for smarter and safer hospitals

Nowadays, during Robotic-Minimally Invasive Surgeries, two surgeons are needed in the operating room:

• the main surgeon, who tele-operates the robotic surgery platform,
• and the assistant surgeon, who uses laparoscopic instruments to provide support during the procedure.

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SARAS will develop a cognitive architecture able to make decisions based on pre-operative knowledge and on scene understanding via advanced machine learning algorithms.

Dexterity and perception capabilities of surgical robots may soon be improved by cognitive functions that can support surgeons in decision making and performance monitoring, and enhance the impact of automation within the operating rooms.

Training platforms, virtual or physical, are a perfect complement to conventional training such as dissection practices that usually provide limited availability and result in high cost. 

SENTISIM User Interface

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Performing ultrasound procedures from a remote site is a challenging task since both a stable behavior, for the safety of the patient, and a high-level of usability, to exploit the sonographer’s expertise, need to be guaranteed.

By ©[2016] Intuitive Surgical, Inc. (©[2016] Intuitive Surgical, Inc.) [CC BY-SA 3.0 (https://creativecommons.org/licenses/by-sa/3.0)], via Wikimedia Commons

The SARAS system will be developed in three increasingly complex platforms.

Each platform implements some of the SARAS results that will be exploited and extended by the next ones.

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