A new subclass of soft robot, known as tip-extending or "vine" robots, consists of long inflatable devices that move through the environment by extending from the tip. A key requirement for many applications of these robots is a working channel-a hollow tube through the core of the robot for passing tools, sensors, fluids, etc. While working channels have been proposed in a few vine robots, it remains an open challenge to create miniaturized vine robots (diameter < 1 cm) with working channels that enable continuous access through the core. In this paper, we analyze the growth models of current vine robot designs and show that the working channel greatly increases required pressure to grow at small scales due to internal friction. Based on this insight, we propose the concept of storing scrunched material at the tip of the vine robot to circumvent this frictional force. We validate our models and demonstrate this concept via prototypes down to diameters of 2.3 mm. Overall, this work enables the creation of miniaturized vine robots with working channels, which significantly enhances their practicality and potential for impact in applications such as minimally invasive surgery.

State estimation from measured data is crucial for robotic applications as autonomous systems rely on sensors to capture the motion and localize in the 3D world. Among sensors that are designed for measuring a robot's pose, or for soft robots, their shape, vision sensors are favorable because they are information-rich, easy to set up, and cost-effective. With recent advancements in computer vision, deep learning-based methods no longer require markers for identifying feature points on the robot. However, learning-based methods are data-hungry and hence not suitable for soft and prototyping robots, as building such bench-marking datasets is usually infeasible. In this work, we achieve image-based robot pose estimation and shape reconstruction from camera images. Our method requires no precise robot meshes, but rather utilizes a differentiable renderer and primitive shapes. It hence can be applied to robots for which CAD models might not be available or are crude. Our parameter estimation pipeline is fully differentiable. The robot shape and pose are estimated iteratively by back-propagating the image loss to update the parameters. We demonstrate that our method of using geometrical shape primitives can achieve high accuracy in shape reconstruction for a soft continuum robot and pose estimation for a robot manipulator.

Concentric tube robots (CTRs) have drawn significant research attention over the years, particularly due to their applications in minimally invasive surgery (MIS). Indeed, their small size, flexibility, and high dexterity enable several potential benefits for MIS. The research has led to an increasing number of discoveries and scientific breakthroughs in CTR design, fabrication, control, and applications. Numerous prototypes have emerged from different research groups, each with its own design and specifications. This survey paper provides an overview of the state of the art of the mechatronics aspects of CTRs, including approaches for the design and fabrication of the tubes, actuation unit, and end effector. In addition to the various hardware and associated fabrication methods, we propose to the research community, a unifying way of classifying CTRs based on their actuation unit architecture, as well as a set of specification details for the evaluation of future CTR prototypes. Finally, we also aim to highlight the current advancements, challenges, and perspectives of CTR design and fabrication.

Concentric tube robots (CTRs) show particular promise for minimally invasive surgery due to their inherent compliance and ability to navigate in constrained environments. Due to variations in anatomy among patients and variations in task requirements among procedures, it is necessary to customize the design of these robots on a patient- or population-specific basis. However, the complex kinematics and large design space make the design problem challenging. In this article, we propose a computational framework that can efficiently optimize a robot design and a motion plan to enable safe navigation through the patient’s anatomy. The current framework is the first fully gradient-based method for CTR design optimization and motion planning, enabling an efficient and scalable solution for simultaneously optimizing continuous variables, even across multiple anatomies. The framework is demonstrated using two clinical examples, laryngoscopy and heart biopsy, where the optimization problems are solved for a single patient and across multiple patients, respectively.

Minimally invasive surgery is of high interest for interventional medicine since the smaller incisions can lead to less pain and faster recovery for patients. The current standard-of-care involves a range of affordable, manual, hand-held rigid tools, whose limited dexterity and range of adoptable shapes can prevent access to confined spaces. In contrast, recently developed roboticized tools that can provide increased accessibility and dexterity to navigate and perform complex tasks often come at the cost of larger, heavier, and grounded devices that are teleoperated, posing a new set of challenges. In this article, we propose a new hand-held concentric tube robot with an associated position control method that has the dexterity and precision of large roboticized devices, while maintaining the footprint of a traditional hand-held tool. The device shows human-in-the-loop control performance that meets the requirements of the targeted application, percutaneous abscess drainage. In addition, a small user study illustrates the advantage of combining rigid body motion of the device with more precise motions of the tip, thus showing the potential to bridge the gap between traditional hand-held tools and grounded robotic devices.

In this paper, we propose to take advantage of concentric tube robots (CTR) properties to design a robotic system for optical biopsies with fiber-based imaging modalities. Follow-the-leader (FTL) deployment, with CTR body following its tip, is being integrated as a design constraint in order to minimize the device invasiveness. A design procedure is proposed and developed in the context of olfactory cell inspection. Stability issues of CTR are considered with theoretical validation of FTL deployment. Finally, an experimental assessment in lab conditions is being conducted that includes the device deployment and the reproduction of scanning task for imaging. The whole surface to be inspected can be accessed, and 20 μm resolution of the CTR tip is observed.