Control devices are essential in shaping the user experience of telepresence robot operators. This is especially true for mobile telemanipulator robots (MTRs), which offer greater opportunities for social interaction compared to mobile or tabletop telepresence robots, but are more difficult to control. This increased difficulty can diminish key aspects of user experience, such as sense of control (SoC), which many users value over performance. However, the usability of telepresence control devices has been critically overlooked in HRI research. In a between-subjects study (n = 63), we investigate how three widely used control devices (mouse, gamepad, haptic controller) affect critical aspects of teleoperation: perceived SoC, safety, usability, and cognitive load; and task performance. Participants remotely controlled an MTR (Stretch) to wait on a customer in a social telepresence setting (cafe). We found that the type of control device significantly impacts both task performance and SoC in direct teleoperation, with the mouse having the best performance/SoC. There were notable tradeoffs in speeds, errors, and task completion times, and participants with higher SoC performed significantly better than those with lower SoC. We provide participant-informed suggestions for future control device design, such as allowing users to reconfigure its physical form, input sensitivity, and controls to align with video game conventions. By foregrounding the role of control devices, our work contributes to ongoing conversations in HRI around the tradeoffs between autonomy, usability, and user agency in social telepresence.

The flexibility and dexterity of cable-driven continuum robots (CDCRs) make them well suited for intricate tasks such as minimally invasive surgery. However, the complexity of accurately modeling their dynamics has limited their broader adoption and effective control. Current models either oversimplify the dynamics by assuming quasi-static conditions or over complicate them, making real-time application challenging. Additionally, many existing models neglect the critical coupling between the robot's body and actuator dynamics, a factor essential for accurate control. In this paper, we propose a new minimal dynamics model for CDCRs that strikes a balance between simplicity and accuracy. Our model captures the essential dynamics of both the robot and its actuators, providing a practical tool for control design. We also establish connections between our model and those used for other robotic systems, enabling the transfer of well-established control strategies to CDCRs. The model is validated through hardware experiments, demonstrating its ability to effectively address complex control challenges in CDCR applications.

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.

Haptic feedback can provide operators of hand-held robots with active guidance during challenging tasks and with critical information on environment interactions. Yet for such haptic feedback to be effective, it must be lightweight, capable of integration into a hand-held form factor, and capable of displaying easily discernible cues. We present the design and evaluation of HaPPArray - a haptic pneumatic pouch array - where the pneumatic pouches can be actuated alone or in sequence to provide information to the user. A 3x3 array of pouches was integrated into a handle, representative of an interface for a hand-held robot. When actuated individually, users were able to correctly identify the pouch being actuated with 86% accuracy, and when actuated in sequence, users were able to correctly identify the associated direction cue with 89 % accuracy. These results, along with a demonstration of how the direction cues can be used for haptic guidance of a medical robot, suggest that HaPPArray can be an effective approach for providing haptic feedback for hand-held robots.

In this work, we address the problem of robust segmentation of a continuum robot from images without the need for training data or markers. We present a method that leverages information about the kinematics of these robots to produce an estimate of the robot shape, which is refined through optimization over global image statistics. Our approach can be straightforwardly applied to any continuum robot design and is able to handle partial occlusions of the robot body, as well as challenging background conditions. We validate our method experimentally for a concentric tube robot in a simulated surgical environment and show that our method significantly outperforms a naive projection of the robot shape and color thresholding, which is commonly used in current vision-based estimation algorithms for these robots. Overall, this work has the potential to improve the viability of vision-based state estimation for continuum robots in real-world settings.

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.

Soft, growing robots have the ability to conform to their environment and traverse highly curved paths that would typically prove challenging for other robot designs. As they navigate through these constrained and cluttered environments, there is often significant interaction between the robot and its surroundings. In this work, we propose a method to enable tactile perception for growing robots, which utilizes commercially available, flexible sensors that measure the curvature of the robot shape at multiple locations. Our method consists of both a pouch design to enable seamless integration of the sensors with the material of the growing robot, as well as an algorithm for determining the location of point contacts along the robot body. We validate our proposed approach experimentally using a 3.5 cm robot that can grow to be 53 cm long. We show that we can localize a force applied to various locations along its length with an average error of$3.444\pm1.38$cm when the robot is unactuated and$4.62\pm 0.95$cm when the robot is actuated. Additionally, we characterize the minimum distance required for our tactile sensing approach to discriminate between two separate contact points along the robot body to be 23.5 cm. Finally, we apply our method to a growing robot exploring an unknown environment and show that we are able to effectively determine when and where the growing robot collides with an unknown obstacle.

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.

We describe a new series pneumatic artificial muscle (sPAM) and its application as an actuator for a soft continuum robot. The robot consists of three sPAMs arranged radially round a tubular pneumatic backbone. Analogous to tendons, the sPAMs exert a tension force on the robot's pneumatic backbone, causing bending that is approximately constant curvature. Unlike a traditional tendon driven continuum robot, the robot is entirely soft and contains no hard components, making it safer for human interaction. Models of both the sPAM and soft continuum robot kinematics are presented and experimentally verified. We found a mean position accuracy of 5.5 cm for predicting the end-effector position of a 42 cm long robot with the kinematic model. Finally, closed-loop control is demonstrated using an eye-in-hand visual servo control law which provides a simple interface for operation by a human. The soft continuum robot with closed-loop control was found to have a step-response rise time and settling time of less than two seconds.

Concentric tube surgical robots are minimally invasive devices with the advantages of snake-like reconfigurability, long and thin form factor, and placement of actuation outside the patient's body. These robots can also be designed and manufactured to acquire targets in specific patients for treating specific diseases in a manner that minimizes invasiveness. We propose that concentric tube robots can be manufactured using 3-D printing technology on a patient- and procedure-specific basis. In this paper, we define the design requirements and manufacturing constraints for 3-D printed concentric tube robots and experimentally demonstrate the capabilities of these robots. While numerous 3-D printing technologies and materials can be used to create such robots, one successful example uses selective laser sintering to make an outer tube with a polyether block amide and uses stereolithography to make an inner tube with a polypropylene-like material. This enables a tube pair with precurvatures of 0.0775 and 0.0455 mm-1, which can withstand strains of 20% and 5.5% for the outer and inner tubes, respectively.