Needle-Tissue Interaction Force State Estimation for Robotic Surgical Suturing

The current state of autonomous suturing: a systematic review

BACKGROUND

Robotic technology is an important tool in surgical innovation, with robots increasingly being used in the clinical setting. Robots can be used to enhance accuracy, perform remote actions, or to automate tasks. One such surgical task is suturing, a repetitive, fundamental component of surgery that can be tedious and time consuming. Suturing is a promising automation target because of its ubiquity, repetitive nature, and defined constraints. This systematic review examines research to date on autonomous suturing.

METHODS

A systematic review of the literature focused on autonomous suturing was conducted in accordance with PRISMA guidelines.

RESULTS

6850 articles were identified by searching PubMed, Embase, Compendex, and Inspec. Duplicates and non-English articles were removed. 4389 articles were screened and 4305 were excluded. Of the 84 remaining, 43 articles did not meet criteria, leaving 41 articles for final review. Among these, 34 (81%) were published after 2014. 31 (76%) were published in an engineering journal9 in a robotics journal, and 1 in a medical journal. The great majority of articles (33, 80%) did not have a specific clinical specialty focus, whereas 6 (15%) were focused on applications in MIS/laparoscopic surgery and 2 (5%) on applications in ophthalmology. Several suturing subtasks were identified, including knot tying, suture passing/needle insertion, needle passing, needle and suture grasping, needle tracking/kinesthesia, suture thread detection, suture needle shape production, instrument assignment, and suture accuracy. 14 articles were considered multi-component because they referred to several previously mentioned subtasks.

CONCLUSION

In this systematic review exploring research to date on autonomous suturing, 41 articles demonstrated significant progress in robotic suturing. This summary revealed significant heterogeneity of work, with authors focused on different aspects of suturing and a multitude of engineering problems. The review demonstrates increasing academic and commercial interest in surgical automation, with significant technological advances toward feasibility.

Data-Driven Robotic Manipulation of Cloth-like Deformable Objects: The Present, Challenges and Future Prospects

Manipulating cloth-like deformable objects (CDOs) is a long-standing problem in the robotics community. CDOs are flexible (non-rigid) objects that do not show a detectable level of compression strength while two points on the article are pushed towards each other and include objects such as ropes (1D), fabrics (2D) and bags (3D). In general, CDOs' many degrees of freedom (DoF) introduce severe self-occlusion and complex state-action dynamics as significant obstacles to perception and manipulation systems. These challenges exacerbate existing issues of modern robotic control methods such as imitation learning (IL) and reinforcement learning (RL). This review focuses on the application details of data-driven control methods on four major task families in this domain: cloth shaping, knot tying/untying, dressing and bag manipulation. Furthermore, we identify specific inductive biases in these four domains that present challenges for more general IL and RL algorithms.

Camera-Robot Calibration for the da Vinci® Robotic Surgery System

The development of autonomous or semi-autonomous surgical robots stands to improve the performance of existing teleoperated equipment, but requires fine hand-eye calibration between the free-moving endoscopic camera and patient-side manipulator arms (PSMs). A novel method of solving this problem for the da Vinci® robotic surgical system and kinematically similar systems is presented. First, a series of image-processing and optical-tracking operations are performed to compute the coordinate transformation between the endoscopic camera view frame and an optical-tracking marker permanently affixed to the camera body. Then, the kinematic properties of the PSM are exploited to compute the coordinate transformation between the kinematic base frame of the PSM and an optical marker permanently affixed thereto. Using these transformations, it is then possible to compute the spatial relationship between the PSM and the endoscopic camera using only one tracker snapshot of the two markers. The effectiveness of this calibration is demonstrated by successfully guiding the PSM end effector to points of interest identified through the camera. Additional tests on a surgical task, namely grasping a surgical needle, are also performed to validate the proposed method. The resulting visually-guided robot positioning accuracy is better than the earlier hand-eye calibration results reported in the literature for the da Vinci® system, while supporting intraoperative update of the calibration and requiring only devices that are already commonly used in the surgical environment.

Autonomous Laparoscopic Robotic Suturing with a Novel Actuated Suturing Tool and 3D Endoscope

Compared to open surgical techniques, laparoscopic surgical methods aim to reduce the collateral tissue damage and hence decrease the patient recovery time. However, constraints imposed by the laparoscopic surgery, i.e. the operation of surgical tools in limited spaces, turn simple surgical tasks such as suturing into time-consuming and inconsistent tasks for surgeons. In this paper, we develop an autonomous laparoscopic robotic suturing system. More specific, we expand our smart tissue anastomosis robot (STAR) by developing i) a new 3D imaging endoscope, ii) a novel actuated laparoscopic suturing tool, and iii) a suture planning strategy for the autonomous suturing. We experimentally test the accuracy and consistency of our developed system and compare it to sutures performed manually by surgeons. Our test results on suture pads indicate that STAR can reach 2.9 times better consistency in suture spacing compared to manual method and also eliminate suture repositioning and adjustments. Moreover, the consistency of suture bite sizes obtained by STAR matches with those obtained by manual suturing.

Robotic manipulation and sensing of deformable objects in domestic and industrial applications: a survey

We present a survey of recent work on robot manipulation and sensing of deformable objects, a field with relevant applications in diverse industries such as medicine (e.g. surgical assistance), food handling, manufacturing, and domestic chores (e.g. folding clothes). We classify the reviewed approaches into four categories based on the type of object they manipulate. Furthermore, within this object classification, we divide the approaches based on the particular task they perform on the deformable object. Finally, we conclude this survey with a discussion of the current state-of-the-art approaches and propose future directions within the proposed classification.

Three-Dimensional Surgical Needle Localization and Tracking Using Stereo Endoscopic Image Streams

This paper presents algorithms for three-dimensional tracking of surgical needles using the stereo endoscopic camera images obtained from the da Vinci ® Surgical Robotic System. The proposed method employs Bayesian state estimation, computer vision techniques, and robot kinematics. A virtual needle rendering procedure is implemented to create simulated images of the surgical needle under the da Vinci ® robot endoscope, which makes it possible to measure the similarity between the rendered needle image and the real needle. A particle filter algorithm using the mentioned techniques is then used for tracking the surgical needle. The performance of the tracking is experimentally evaluated using an actual da Vinci ® surgical robotic system and quantitatively validated in a ROS/Gazebo simulation thereof.