100 research outputs found
A Biomimetic steering robot for Minimally invasive surgery application
International audienceMinimally Invasive Surgery represents the future of many types of medical inter- ventions such as keyhole neurosurgey or transluminal endoscopic surgery. These procedures involve insertion of surgical instruments such as needles and endoscopes into human body through small incision/ body cavity for biopsy and drug delivery. However, nearly all surgical instruments for these procedures are inserted manually and there is a long learning curve for surgeons to use them properly. Many research efforts have been made to design active instruments (endoscope, needles) to improve this procedure during last decades. New robot mechanisms have been designed and used to improve the dexterity of current endoscope. Usually these robots are flexible and can pass the constrained space for fine manipulations. In recent years, a con- tinuum robotic mechanism has been investigated and designed for medical surgery. Those robots are characterized by the fact that their mechanical components do not have rigid links and discrete joints in contrast with traditional robot manipula- tors. The design of these robots is inspired by movements of natural animals such as tongues, elephant trunks and tentacles. The unusual compliance and redundant degrees of freedom of these robots provide strong potential to achieve delicate tasks successfully even in cluttered and unstructured environments. This chapter will present a complete application of a continuum robot for Mini- mally Invasive Surgery of colonoscopy. This system is composed of a micro-robotic tip, a set of position sensors and a real-time control system for guiding the explo- ration of colon. Details will be described on the modeling of the used pneumatic actuators, the design of the mechanical component, the kinematic model analysis and the control strategy for automatically guiding the progression of the device inside the human colon. Experimental results will be presented to check the perfor- mances of the whole system within a transparent tube
Robot Autonomy for Surgery
Autonomous surgery involves having surgical tasks performed by a robot
operating under its own will, with partial or no human involvement. There are
several important advantages of automation in surgery, which include increasing
precision of care due to sub-millimeter robot control, real-time utilization of
biosignals for interventional care, improvements to surgical efficiency and
execution, and computer-aided guidance under various medical imaging and
sensing modalities. While these methods may displace some tasks of surgical
teams and individual surgeons, they also present new capabilities in
interventions that are too difficult or go beyond the skills of a human. In
this chapter, we provide an overview of robot autonomy in commercial use and in
research, and present some of the challenges faced in developing autonomous
surgical robots
Surgical Subtask Automation for Intraluminal Procedures using Deep Reinforcement Learning
Intraluminal procedures have opened up a new sub-field of minimally invasive surgery that use flexible instruments to navigate through complex luminal structures of the body, resulting in reduced invasiveness and improved patient benefits. One of the major challenges in this field is the accurate and precise control of the instrument inside the human body. Robotics has emerged as a promising solution to this problem. However, to achieve successful robotic intraluminal interventions, the control of the instrument needs to be automated to a large extent. The thesis first examines the state-of-the-art in intraluminal surgical robotics and identifies the key challenges in this field, which include the need for safe and effective tool manipulation, and the ability to adapt to unexpected changes in the luminal environment. To address these challenges, the thesis proposes several levels of autonomy that enable the robotic system to perform individual subtasks autonomously, while still allowing the surgeon to retain overall control of the procedure. The approach facilitates the development of specialized algorithms such as Deep Reinforcement Learning (DRL) for subtasks like navigation and tissue manipulation to produce robust surgical gestures. Additionally, the thesis proposes a safety framework that provides formal guarantees to prevent risky actions. The presented approaches are evaluated through a series of experiments using simulation and robotic platforms. The experiments demonstrate that subtask automation can improve the accuracy and efficiency of tool positioning and tissue manipulation, while also reducing the cognitive load on the surgeon. The results of this research have the potential to improve the reliability and safety of intraluminal surgical interventions, ultimately leading to better outcomes for patients and surgeons
Efficient RRT*-based Safety-Constrained Motion Planning for Continuum Robots in Dynamic Environments
Continuum robots, characterized by their high flexibility and infinite
degrees of freedom (DoFs), have gained prominence in applications such as
minimally invasive surgery and hazardous environment exploration. However, the
intrinsic complexity of continuum robots requires a significant amount of time
for their motion planning, posing a hurdle to their practical implementation.
To tackle these challenges, efficient motion planning methods such as Rapidly
Exploring Random Trees (RRT) and its variant, RRT*, have been employed. This
paper introduces a unique RRT*-based motion control method tailored for
continuum robots. Our approach embeds safety constraints derived from the
robots' posture states, facilitating autonomous navigation and obstacle
avoidance in rapidly changing environments. Simulation results show efficient
trajectory planning amidst multiple dynamic obstacles and provide a robust
performance evaluation based on the generated postures. Finally, preliminary
tests were conducted on a two-segment cable-driven continuum robot prototype,
confirming the effectiveness of the proposed planning approach. This method is
versatile and can be adapted and deployed for various types of continuum robots
through parameter adjustments
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Chip-on-tip endoscope incorporating a soft robotic pneumatic bending microactuator.
In the ever advancing field of minimally invasive surgery, flexible instruments with local degrees of freedom are needed to navigate through the intricate topologies of the human body. Although cable or concentric tube driven solutions have proven their merits in this field, they are inadequate for realizing small bending radii and suffer from friction, which is detrimental when automation is envisioned. Soft robotic actuators with locally actuated degrees of freedom are foreseen to fill in this void, where elastic inflatable actuators are very promising due to their S3-principle, being Small, Soft and Safe. This paper reports on the characterization of a chip-on-tip endoscope, consisting out of a soft robotic pneumatic bending microactuator equipped with a 1.1 × 1.1 mm2 CMOS camera. As such, the total diameter of the endoscope measures 1.66 mm. To show the feasibility of using this system in a surgical environment, a preliminary test on an eye mock-up is conducted
A disposable continuum endoscope using piston-driven parallel bellow actuator
This paper presents a novel low cost disposable continuum endoscope based on a piston-driven parallel bellow actuator design. The parallel bellow actuator achieves motion by being pressurized via displacement-controlled pistons. The displacements are generated by rack-and-pinion mechanisms using inexpensive stepper motors. The design concept provides a potential alternative solution to upper gastrointestinal (UGI) diagnosis. The modularity and the use of inexpensive components allow for low fabrication costs and disposability. The use of robotic assistance could facilitate the development of an easier interface for the gastroenterologists, avoiding the nonintuitive manipulation mapping of the traditional UGI endoscopes. We adapt existing kinematic solutions of multi-backbone continuum robots to model continuum parallel bellow actuators. An actuation compensation strategy is presented and validated to address the pneumatic compressibility through the transmission lines. The design concept was prototyped and tested with a custom control platform. The experimental validation shows that the actuation compensation was demonstrated to significantly improve orientation control of the endoscope end-effector. This paper shows the feasibility of the proposed design and lays the foundation toward clinical scenarios
Soft Pneumatic Actuator Skin with Embedded Sensors
Soft Pneumatic Actuator skin (SPA-skin) is a novel concept of ultra-thin (< 1 mm) sensor embedded actuators with distributed actuation points that could cover soft bodies. This highly customizable and flexible SPA-skin is ideal for providing proprioceptive sensing by covering pre-existing structures and robots bodies. Having few limitation of the surface quality, dynamics, or shape, these mechanical attributes allow potential applications in autonomous flexible braille, active surface pattern reconfiguration, distributed actuation and sensing for tactile interface improvements. In this paper, the authors present a proof-of-concept SPA-skin. The mechanical parameters, design criteria, sensor selection, and actuator construction process are illustrated. Two control schemes, actuation mode and force sensing mode, are also demonstrated with the latest prototype
Design and control of a novel variable stiffness soft arm
Soft robot arms possess such characteristics as light weight, simple structure and good adaptability to the
environment, among others. On the other hand, robust control of soft robot arms presents many difficulties. Based
on these reasons, this paper presents a novel design and modelling of a fuzzy active disturbance rejection control
(FADRC) controller for a soft PAM arm. The soft arm comprises three contractile and one extensor PAMs, which
can vary its stiffness independently of its position in space. Force analysis for the soft arm is conducted, and stiffness
model of the arm is established based on the relational model of contractile and extensor PAM. The accuracy of
stiffness model for the soft arm was verified through experiments. Associated to this, a controller based on the fuzzy
adaptive theory and ADRC, FADRC, has been designed to control the arm. The fuzzy adaptive theory is used to
adjust the parameters of the ADRC, the control algorithm has the ability to control stiffness and position of the soft
arm. In this paper, FADRC was further verified through comparative experiments on the soft arm. This paper
reinforces the hypothesis that FADRC control, as an algorithm, indeed possesses good robustness and adaptive
abilities.
Key words: soft robot, variable stiffness, PAM, stiffness modelling, FADR
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