Virtual interactive suturing for the Fundamentals of Laparoscopic Surgery (FLS)

BACKGROUND

Suturing with intracorporeal knot-tying is one of the five tasks of the Fundamentals of Laparoscopic Surgery (FLS), which is a pre-requisite for board certification in general surgery. This task involves placing a short suture through two marks in a penrose drain and then tying a double-throw knot followed by two single-throw knots using two needle graspers operated by both hands. A virtual basic laparoscopic skill trainer (VBLaST©) is being developed to represent the virtual versions of the FLS tasks, including automated, real time performance measurement and feedback. In this paper, we present the development of a VBLaST suturing simulator (VBLaST-SS©). Developing such a simulator involves solving multiple challenges associated with fast collision detection, response and force feedback.

METHODS

In this paper, we present a novel projection-intersection based knot detection method, which can identify the validity of different types of knots at haptic update rates. A simple and robust edge-edge based collision detection algorithm is introduced to support interactive knot tying and needle insertion operations. A bimanual hardware interface integrates actual surgical instruments with haptic devices enabling not only interactive rendering of force feedback but also realistic sensation of needle grasping, which realizes an immersive surgical suturing environment.

RESULTS

Experiments on performing the FLS intracorporeal suturing task show that the simulator is able to run on a standard personal computer at interactive rates.

CONCLUSIONS

VBLaST-SS© is a computer-based interactive virtual simulation system for FLS intracorporeal knot-tying suturing task that can provide real-time objective assessment for the user's performance.

Learning from Observation Paradigm: Leg Task Models for Enabling a Biped Humanoid Robot to Imitate Human Dances

This paper proposes a framework that achieves the Learning from Observation paradigm for learning dance motions. The framework enables a humanoid robot to imitate dance motions captured from human demonstrations. This study especially focuses on leg motions to achieve a novel attempt in which a biped-type robot imitates not only upper body motions but also leg motions including steps. Body differences between the robot and the original dancer make the problem difficult because the differences prevent the robot from straightforwardly following the original motions and they also change dynamic body balance. We propose leg task models, which play a key role in solving the problem. Low-level tasks in leg motion are modelled so that they clearly provide essential information required for keeping dynamic stability and important motion characteristics. The models divide the problem of adapting motions into the problem of recognizing a sequence of the tasks and the problem of executing the task sequence. We have developed a method for recognizing the tasks from captured motion data and a method for generating the motions of the tasks that can be executed by existing robots including HRP-2. HRP-2 successfully performed the generated motions, which imitated a traditional folk dance performed by human dancers.

Quasi-static manipulation of a Kirchhoff elastic rod based on a geometric analysis of equilibrium configurations

Consider a thin, flexible wire of fixed length that is held at each end by a robotic gripper. Any curve traced by this wire when in static equilibrium is a local solution to a geometric optimal control problem, with boundary conditions that vary with the position and orientation of each gripper. We prove that the set of all local solutions to this problem over all possible boundary conditions is a smooth manifold of finite dimension that can be parameterized by a single chart. We show that this chart makes it easy to implement a sampling-based algorithm for quasi-static manipulation planning. We characterize the performance of such an algorithm with experiments in simulation.

Topology-based representations for motion planning and generalization in dynamic environments with interactions

Motion can be described in several alternative representations, including joint configuration or end-effector spaces, but also more complex topology-based representations that imply a change of Voronoi bias, metric or topology of the motion space. Certain types of robot interaction problems, e.g. wrapping around an object, can suitably be described by so-called writhe and interaction mesh representations. However, considering motion synthesis solely in a topology-based space is insufficient since it does not account for additional tasks and constraints in other representations. In this paper, we propose methods to combine and exploit different representations for synthesis and generalization of motion in dynamic environments. Our motion synthesis approach is formulated in the framework of optimal control as an approximate inference problem. This allows for consistent combination of multiple representations (e.g. across task, end-effector and joint space). Motion generalization to novel situations and kinematics is similarly performed by projecting motion from topology-based to joint configuration space. We demonstrate the benefit of our methods on problems where direct path finding in joint configuration space is extremely hard whereas local optimal control exploiting a representation with different topology can efficiently find optimal trajectories. In real-world demonstrations, we highlight the benefits of using topology-based representations for online motion generalization in dynamic environments.

A novel knot-tying approach for minimally invasive surgical robot systems

BACKGROUND

In robot-assisted minimally invasive surgery (MIS), knot-tying is an important but challenging task for surgeons when performing surgery by manipulating a master-slave robot system. Knot-tying in the conventional way is restricted by a confined workspace, which may cause the suture loop to be unstable and make knot-tying difficult and time-consuming in robot-assisted MIS.

METHODS

A knot-tying approach named 'bending-twisting knot-tying' (BTKT) has been developed for robot-assisted surgery systems operating in a confined workspace. The non-linear deformation of sutures during knot-tying is qualitatively described using knot theory. The length ratio of a knot (LoK) and the feasible coefficient (Fc) are introduced to evaluate the quality of BTKT knots. Simulations and experiments are performed based on finite segment dynamic models and the MicroHand surgical system, respectively, to describe the dynamic behaviours of the knots. Sensitive parameters, including the length of a suture (L), the distance between two ends (d) and the angle between tangents of the two ends (alpha) are analysed based on the model.

RESULTS

For a terylene suture, the length of the suture L and the distance between the two ends d should satisfy 1.12d< or =L< or =14.4d. When L and alpha are constant, the smaller d is, the larger are LoK and Fc relative to different sutures. A knot of high quality can be tied with a small alpha.

CONCLUSIONS

Simulation and experimental results show that BTKT requires a smaller workspace and can form more stable loops compared to conventional methods.