Tania K. Morimoto

Continuum robots are well suited for navigating confined and fragile environments, such as vascular or endoluminal anatomy, where contact with surrounding structures is often unavoidable. While controlled contact can assist motion, unfavorable contact can degrade controllability, induce kinematic singularities, or introduce safety risks. We present a contact-aware planning approach that evaluates contact quality, penalizing hazardous interactions, while permitting benign contact. The planner produces kinematically feasible trajectories and contact-aware Jacobians which can be used for closed-loop control in hardware experiments. We validate the approach by testing the integrated system (planning, control, and mechanical design) on anatomical models from patient scans. The planner generates effective plans for three common anatomical environments, and, in all hardware trials, the continuum robot was able to reach the target while avoiding dangerous tip contact (100% success). Mean tracking errors were 1.9 +/- 0.5 mm, 1.2 +/- 0.1 mm, and 1.7 +/- 0.2 mm across the three different environments. Ablation studies showed that penalizing end-of-continuum-segment (ECS) contact improved manipulability and prevented hardware failures. Overall, this work enables reliable, contact-aware navigation in highly constrained environments.

Continuum robots are well suited for navigating confined and fragile environments, such as vascular or endoluminal anatomy, where contact with surrounding structures is often unavoidable. While controlled contact can assist motion, unfavorable contact can degrade controllability, induce kinematic singularities, or introduce safety risks. We present a contact-aware planning approach that evaluates contact quality, penalizing hazardous interactions, while permitting benign contact. The planner produces kinematically feasible trajectories and contact-aware Jacobians which can be used for closed-loop control in hardware experiments. We validate the approach by testing the integrated system (planning, control, and mechanical design) on anatomical models from patient scans. The planner generates effective plans for three common anatomical environments, and, in all hardware trials, the continuum robot was able to reach the target while avoiding dangerous tip contact (100% success). Mean tracking errors were 1.9 +/- 0.5 mm, 1.2 +/- 0.1 mm, and 1.7 +/- 0.2 mm across the three different environments. Ablation studies showed that penalizing end-of-continuum-segment (ECS) contact improved manipulability and prevented hardware failures. Overall, this work enables reliable, contact-aware navigation in highly constrained environments.

Soft growing robots offer a promising solution for deployment in confined and unstructured environments due to their unique locomotion principles. Although this approach has revolutionized the way robots can navigate lumens of varying diameters and shapes, steering these robots remains challenging-especially at bifurcations or when navigating toward specific targets in open-space environments. While ongoing research continues to improve steering capabilities, the shape of soft growing robots is still largely dictated by their surrounding environment. This study addresses this fundamental limitation by extending the concept of magnetic steering previously introduced in the literature. We propose a new approach that employs an embedded magnetic signature to enable full-body shape deformation. Based on a physical model that combines magneto-elasticity with the eversion growth principle, we also introduce a method for shape sensing and demonstrate the concept of pressure-free growth. The robot’s magnetic signature is defined along the $\mathbf{X}$ and $\mathbf{Y}$ axes, while local magnetization along the Z axis enables shape sensing. As a proof of concept, the proposed soft growing robot has a diameter of 1.8 mm and can evert over a length of 6 cm. It incorporates two submillimeter 3D Hall-effect sensors for real-time shape sensing, a camera, and a cytology brush that can be deployed from the inner channel for biome sampling. The robot can grow without internal pressure, be magnetically steered in open space to reach complex configurations such as retroflexion, and its shape can be sensed at frequencies up to 500 Hz.

The steering ability of vine robots becomes increasingly crucial when navigating highly tortuous and constrained environments. In this study, we enhance the passive steering ability of vine robots by introducing shape changes induced by pressure differences through a bilayer tube design with slits, which we call the Contraction Vine Robot (CVR). Upon pressurization, the robot undergoes localized radial expansion and longitudinal contraction. By applying pressure oscillation, repeated changes in robot shape and length enables the robot tip to slide from the obstacle and continue to navigate. We established both static and geometric models to describe how radial expansion and longitudinal contraction occur under internal pressure and validated these models against experimental data. We also investigated the steering capabilities of the proposed robot design in various obstacle conditions and compared the results with a conventional vine robot. The results showed that compared to the conventional vine robot, our robot exhibited substantially superior performance along bumpy, tortuous paths.

Vine robots at a millimeter-scale enable safe and adaptive navigation through confined and delicate environments such as inside the human body. However, accurate modeling and control remain challenging due to nonlinear material behavior, hysteresis, and complex environmental interactions. This work presents a data-driven framework for modeling and control of millimeter-scale vine robots. By leveraging a tracking method that uses visual fiducial markers (AprilTags), we demonstrated accurate and robust tracking of the tip without affecting the performance of the robot. We trained a neural network to predict the position of the tip of the robot in the next timestep based on the actuation and previous states of the robot. A feedforward control algorithm built on this model enabled autonomous trajectory following of a 5 mm diameter vine robot, achieving a root mean square error of 5.17 mm. These results demonstrate the potential of data-driven approaches for achieving accurate modeling and autonomous control of small-scale vine robots.

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.

Teleoperating mobile manipulators can be cognitively demanding due to a lack of depth perception and situational awareness. While virtual fixture constraints can be used to improve teleoperation performance, it is critical to ensure safety of these fixtures in order to enable their use in physical human-robot-interaction (pHRI) tasks. In this work, we propose to use control barrier functions (CBF) to design a virtual fixture architecture that allows us to tune the tradeoff between performance and safety. We design the architecture to ensure tracking performance between the user and robot is maintained outside of virtual fixture violations, and to simultaneously ensure that the robot cannot overshoot into a constraint. We conducted a theoretical and experimental analysis to investigate the relationship between tracking and safety, and present results which indicate that the ratio between the control gain used for tracking and the safety decay rate determine when the CBF filter and CBF-based force feedback become active. Finally, we implemented our proposed virtual fixture architecture on a mobile manipulator platform to investigate its effects on user's performance as they performed a simulated temperature scanning task. Overall, this work highlights the potential benefits of using CBF-based haptic virtual fixtures for conducting pHRI tasks.

Soft everting robots grow their body from the tip via eversion, enabling minimal interaction with their surroundings. They can traverse complex environments by changing the growth direction via integrated steering mechanisms. However, it is challenging to miniaturize existing steering mechanisms and to achieve multiple bends while remaining fully soft. In this work, we present an approach to create millimeter-scale, steerable, and fully soft everting robots by functionalizing the robot skin with liquid crystal elastomer (LCE) actuators. This design enables large bending angles (>100°) at multiple points along the robot's length. We investigate the effects of internal pressure and actuator temperature as control inputs for steering and demonstrate the potential of our design for practical applications, such as surgical procedures and inspection tasks. Our results highlight the advantages of soft, functionalized skins and represent a step toward small, steerable, soft everting robots for applications in delicate and constrained environments.

Liquid crystal elastomer (LCE) is a promising material to develop thermally-driven soft actuators due to its high force density, large elastic strain limit, and mechanically programmable nature. However, the complex trade-off between the force generated and the response speed (i.e., cooling rate), along with the lack of systematic design guidelines necessary to design such actuators using LCE, has significantly limited its widespread adoption for soft robotic applications at the mesoscale (cm-scale). In this work, we developed thermally-driven soft actuators by bundling LCE units with integrated cooling that increased the response speed by over 400% when compared to relying only on passive cooling. We developed and experimentally validated an electro-thermo-mechanical model to predict the force and cooling rate of our actuator and established systematic design guidelines to build our actuators for different soft robotic applications. Using our proposed guidelines, we present an inchworm inspired locomotion robot with a top speed of 6 body lengths per minute. We also present a textile forearm cuff with integrated haptic feedback that can provide up to 4 mm of skin stretch feedback with a cooling rate of 1 second. Overall, the presented actuator, experimental results, and design guidelines expand the potential use cases for thermally-driven actuators in soft robotic applications at the mesoscale.

Endovascular surgeries generally rely on push-based catheters and guidewires, which require significant training to master and can still result in high stress being exerted on the anatomy, especially in tortuous paths. Because these procedures are so technically challenging to perform, many patients have limited access to high-quality treatment. Although various robotic systems have been developed to enhance navigation capabilities, they can also apply high stresses due to sliding against the vascular walls, impeding movement and raising the risk of vascular damage. Soft growing robots offer a promising alternative since their method of movement via eversion minimizes interaction forces with the environment and enables follow-the-leader navigation through tortuous paths. However, reliable steering of small-scale growing robots remains a significant challenge. We propose a robot architecture that combines a hydraulically-actuated, soft growing robot with a soft, tendon-driven notched continuum robot to overcome the challenges of steering for small-scale growing robots in endovascular procedures. The soft notched continuum robot successfully steers around the most difficult aortic arch type, and a 2.67 mm diameter growing robot-comparable in size to current catheters-deploys from the tip, pulling an aspiration catheter through extremely tortuous vessels. We present the design, manufacturing, and control of the notched continuum robot, growing robot, and proximal actuation subsystem. Overall, this robotic architecture facilitates active steering in proximal anatomy and navigation in tortuous distal vessels, with potential to reduce procedure times and expand access to care.

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.

Tracking human movement is essential during robot-assisted rehabilitation to provide kinematic feedback for monitoring range of motion, counting repetitions of a certain movement, or achieving closed-loop control. Current strategies for tracking and analyzing human motion, however, are costly, not easily accessible, or challenging to integrate with existing soft assistive robots. In this work, we present skin-tight sensing garments using commercial flex sensors that can be rapidly manufactured using a sew-free lamination strategy. We designed and fabricated sensing garments that can be worn underneath an existing soft robotic wrist orthosis to provide kinematic feedback on flexion and extension of the wrist. We conducted preliminary experiments and demonstrated that our sensing garment can track the position of the wrist with less than 5° of root mean squared error (RMSE) when compared to motion capture. We also demonstrated that our garment design and fabrication approach can be easily extended to other joints and rehabilitation devices to track uniaxial motions by developing a sensing garment for the index finger to provide kinematic feedback when used with a commercial soft rehabilitation glove. Our sensing garments are easy to manufacture, consist of inexpensive and readily available materials, and show promise as a method for providing real-time kinematic feedback of the user during robot-assisted rehabilitation activities.

Vine robots enable safe navigation through sensitive environments due to their inherent compliance and their mechanism for growth via tip eversion. However, the compliance of these soft robots limits their ability to withstand significant loads, preventing them from performing tasks that require lifting or manipulating objects. To expand the range of applications for vine robots, they must therefore be able to increase their stiffness to prevent collapse. In this paper, we present a low profile, active stiffening mechanism integrated into the skin of the vine robot. The mechanism consists of a set of axially stacked pneumatic pouches that generate an axial force in the robot's body to mitigate wrinkling in the robot's material, enabling the robot to withstand larger loads without collapsing. We characterized the burst pressure, stiffness, and transverse collapse load of the vine robot with our stiffening mechanism and demonstrated the ability of the robot to simultaneously stiffen and grow. Our active stiffening mechanism is implemented in an 18 mm diameter vine robot and achieves a 680% increase in stiffness.

Retraction of soft everting robots via material inversion enables minimal interaction between the robot and the environment, as well as repeated growth and retraction for navigating through complex paths. However, existing retraction strategies are limited to larger-scale robots and often require integration of rigid components. In this work, we present a retraction mechanism for millimeter-scale, soft everting robots enabled by a kinked air channel. The flat air channel is attached to the robot body and kinked at the tip. This kink blocks the air flowing through the channel, allowing the pressure to effectively apply a retraction force at the tip for buckling-free retraction. We developed and validated a model by characterizing the robot at various scales and studying the effectiveness of the kinked air channel for retraction. We demonstrated the robot's retraction capability in several challenging environments, highlighting the benefits of the small size and softness of the retraction mechanism.

Everting soft robots, or vine robots, can navigate delicate, constrained environments with minimal friction. These robots extend from the tip when pressurized, enabling forward motion, however, they require additional actuators to actively steer. Previous works have investigated the use of external magnetic fields, the integration of various pneumatic artificial muscles, and the use of tendon-driven mechanisms to enable active steering. Here, we present an alternative steering approach for vine robots based on the integration of a thermally actuating polymer, liquid crystal elastomer (LCE). We propose a design and fabrication approach to ensure localized bending of the robot and characterize the resulting steering capabilities, including the response time and the achievable bending angle as the pressure inside the robot is varied. The design consisted of independent LCE-heater units integrated at discrete locations along the robot body. When the LCE actuator was heated, the robot could achieve a wide range of bending angles from 8.5° to 57.0° by modulating the internal pressure from 14.89 to 2.76 kPa, respectively. The time required for the LCE to fully actuate was approximately 4 minutes. The performance suggested that soft steerable vine robots with actuating polymer can be used to navigate curved or branching environments.

Many wearable soft robotic devices have been developed to assist with spasticity – the increased muscle tone seen in individuals with neurological conditions such as stroke or cerebral palsy. However, these devices typically lack the ability to individually assist multiple degrees of freedom (DOF), which is essential to performing a broad range of daily tasks. To address this need, we developed a soft robotic thumb orthosis to achieve movement in three DOF. We focused on the thumb as it performs the most complex movement. Our orthosis used three unfolding textile pneumatic actuators to assist with the extension of the interphalangeal joint, combined extension of the metacarpal and carpometacarpal joints, and abduction of the carpometacarpal joint. The orthosis was tested on both a 3D-printed biomimetic test bed that emulated spasticity and a healthy individual. The orthosis met the full range of motion targets for each joint, except for the abduction of the carpometacarpal joint with medium spasticity, and surpassed the range of motion threshold required for activities of daily living. The orthosis was able to: (1) assist each DOF independently, (2) move the tip of a biomimetic thumb to a pre-determined target with total error of less than 1.5 cm when actuated with open-loop control, and, (3) provide individual joint assistance to a user with no motor impairment. This research showcases the ability of a soft robotic orthosis to assist movement in simulated spasticity of individual thumb joints and provides an important step towards a platform to study whether independent joint assistance during rehabilitation improves patient outcomes.

Most commercially available haptic interfaces lack grip force feedback, which can hinder users' ability to properly judge the amount of force applied to virtual or remote objects. Recent work has explored the creation of grip force feedback devices that operate using electromechanical actuators. However, the reliance on motors and rigid components tend to result in bulky or heavy devices. In this work, we present the Haptic Origami Grasper (HaptOGrasp)- a novel lightweight, origami haptic grasper that renders kinesthetic grip force feedback via pneumatic actuation. The actuator takes the form of the Yoshimura origami pattern, which allows for linear expansion and compression. At varying grasp widths, air pressure is adjusted to reliably render between 0 N to 8 N of force to mimic normal forces felt when grasping objects. We conducted a preliminary user study, in which participants used HaptOGrasp to grip a virtual object with a specified level of force, demonstrating the potential of the device to help with telemanipulation tasks requiring specific target forces during grasping.

Vine robots are soft robots that translate by everting, or growing, from their tips. This mechanism of translation minimizes the application of shear forces on the environment, making them particularly well-suited for surgical tasks, such as colonoscopy. However, steering and retracting vine robots within tortuous and delicate environments presents significant challenges. In this article, we introduce a novel soft robotic system for colonoscopy that consists of an inchworm-inspired device—the InchIGRAB—nested within a vine robot. The InchIGRAB is designed to enable steering of the vine robot along curved paths, as well as to enable controlled retraction of the vine robot after it reaches its target. We present the design, modeling, and fabrication of the robotic system and characterize its performance. Furthermore, we demonstrate the presented robotic system's ability to safely navigate the entire colon length, including several curved sections, during both forward motion and retraction, highlighting its potential as a robotic colonoscope that offers enhanced safety for patients.

Cutaneous haptic feedback provides a sense of touch by displaying sensations — such as vibration, skin stretch, or normal force — directly to the skin. While the majority of these devices have been designed to display one main haptic sensation, recent work has begun to explore the creation of multi-modal haptic devices, capable of rendering a variety of cutaneous cues. In this work, we investigate using the tip and body of a continuum robot to directly render multiple cutaneous cues to the fingerpad. We present the design of a device that consists of two Haptic Continuum Robots (HCRs) that is capable of rendering four distinct haptic cues— skin stretch, skin slip, normal indentation, and vibration. We present and validate a model of the proposed HCR and characterize the device performance. Finally, we conduct a preliminary haptic sensation identification study, which showed that users were able to correctly identify the displayed haptic sensation with 90% accuracy.

Soft robots are well suited for various applications, including wearable robotics, haptic devices, and medical robotics, due to their inherent compliance. While there are many methods for actuating soft robots, pneumatic actuation remains the dominant choice because it enables large force output and a fast response time. However, actuating a robot with multiple independent pneumatic actuators requires an equal number of pressure regulators and associated electromechanical components, making the back-end control setup bulky, expensive, and unsuitable for potential untethered applications. In this work, we present PneuSIC Box, a pneumatic demultiplexer inspired by the working principle of a music box. Unlike other pneumatic demultiplexing methods that require many pneumatic and control inputs based on the number of actuators, PneuSIC Box operates with just a single pneumatic input and a motor. Furthermore, PneuSIC Box enables simultaneous control of multiple actuators and allows pneumatic memory retention in the attached actuators without any energy expenditure due to the use of soft kink valves. We discuss the working principle and design of the device, provide a finite element analysis (FEA) model to aid in the design of the kink valves, and present detailed device characterization. Finally, we demonstrate the device's applicability using an inchworm-like robot and a robotic hand with soft fingers.

This paper presents two model-free control strategies for the rejection of unknown disturbances in continuum robots. The strategies utilize a neural network-based approximation technique to estimate the uncertain Jacobian matrix using position measurements. The first strategy is designed for periodic disturbances and employs an adaptive model-free controller in conjunction with an adaptive disturbance observer. The second strategy is designed for robustness against arbitrary disturbances and employs time-varying input and update law gains that grow monotonically, resulting in the achievement of asymptotic, exponential, and prescribed-time reference trajectory tracking. The notion of fixed-time stabilization in prescribed time is particularly noteworthy, as it allows for the predefinition of a terminal time, independent of initial conditions and system parameters. A formal stability analysis is presented for each strategy, and the strategies are both tested experimentally with a concentric tube robot subject to unknown disturbances.

OBJECTIVE: We sought to validate a laryngeal simulation model and subsequently demonstrate its efficacy in improving surgical technique. STUDY DESIGN: Pre-post interventional study. SETTING: Otolaryngology Program at a Tertiary Care Center. METHODS: A low-cost, high-fidelity laryngeal model was created using a 3-dimensional-printed cast and multilayered silicone to mimic vocal fold lesions. Participants (attendings and trainees) were first given a series of tasks including mucosal vocal fold lesion resection and microflap excision of a submucosal lesion. Trainees were then provided with an instructional video from a laryngologist and asked to repeat the same tasks on the model. Performance data was then assessed using validated surveys and blinded expert reviewers. RESULTS: Eighteen participants completed the simulation. All subjects agreed that the "simulation experience was useful" and 93% agreed "the simulator helped improve my ability to do microsurgical tasks." In the postinstruction self-evaluation, trainees reported a significant decrease in mental demand (95% confidence interval [CI]: 0.37-0.91; P = .038) and significant increase in subjective performance (95% CI: 1.51-51.89; P = .016) compared to the preinstruction self-evaluation. On the postinstruction attempt, there was a significant improvement in all domains of the adapted objective structured assessment of technical skills as measured by 3 blinded, expert reviewers. DISCUSSION: This study demonstrates the usefulness of a silicone larynx model and the value of instructional video in developing laryngeal microsurgical skills. Participants positively reviewed the laryngeal model and trainees saw both a subjective and objective improvement indicating tangible operative benefits from the use of this laryngeal simulation.

Concentric tube robots (CTRs) are well-suited to address the unique challenges of minimally invasive surgical procedures due to their small size and ability to navigate highly constrained environments. However, uncertainties in the manufacturing process can lead to challenges in the transition from simulated designs to physical robots. In this work, we propose an end-to-end design workflow for CTRs that considers the often-overlooked impact of manufacturing uncertainty, focusing on two primary sources - tube curvature and diameter. This comprehensive approach incorporates a two-step design optimization and an uncertainty-based selection of manufacturing tolerances. Simulation results highlight the substantial influence of manufacturing uncertainties, particularly tube curvature, on the physical robot's performance. By integrating these uncertainties into the design process, we can effectively bridge the gap between simulation and real-world performance. Two hardware experiments validate the proposed CTR design workflow. The first experiment confirms that the performance of the physical robot lies within the simulated probability distribution from the optimization, while the second experiment demonstrates the feasibility of the overall system for use in micro-laryngeal surgical tasks. This work not only contributes to a more comprehensive understanding of CTR design by addressing manufacturing uncertainties, but also creates a new framework for robust design, as illustrated in the context of micro-laryngeal surgery.

Concentric tube robots (CTRs) are miniaturized continuum robots that are promising for robotic minimally invasive surgeries. Control methods to date have primarily focused on controlling the robot tip. However, small changes in the tip position can result in large deviations in the shape of the robot body, motivating the need for shape control to ensure safe navigation in constrained environments. One proposed method for shape control, known as follow-the-leader (FTL) motion, allows the robot to deploy while occupying minimal volume but is limited to specific CTR designs and deployment sequences. In this letter, we propose a shape control method that approximates FTL motion and is applicable to arbitrary tip navigation tasks without requiring a predefined trajectory or specific tube design. This shape control method is framed as a nonlinear optimization problem, and through linearization of the CTR's kinematics, we turn it into a quadratic program solved by a shape controller that requires minimal knowledge of the robot's shape. Simulations show that our method enables better approximate FTL motion compared to a state-of-the-art Jacobian-based tip controller across different tube sets and tip paths while remaining computationally comparable. Furthermore, a hardware demonstration validates the effectiveness of the shape controller on a physical system during teleoperation.

Vine robots are a form of soft continuum robot formed of a thin-wall cylinder which has been partially inverted. When pressure is applied internally, the inverted material is propelled outwards causing the body to extend [1] (See Figure 1). This unique form of navigation facilitates shear-free locomotion and high tip force, leading to their proposed use in endoluminal interventions [2]. These properties have the potential to minimize potential traumatic tissue interactions and, due to their inherent minaturizability, facilitate navigation deep within the anatomy. When pressure is applied, vine robots intrinsically follow the forward path of least resistance, passively navigating around obstacles and forming curvatures in their everted body. However, these robots lack the ability to steer their direction of growth in the absence of additional mecha- nisms. Steering methodologies such as series pneumatic artificial muscles employ expanding actuators along the length of the robot. These offer modest deformation but preserve the soft structure of the robot body [1], [3]. Alternative approaches include tendon-driven designs which provide much greater angles of curvature however sacrifice the fully-soft structure [2]. The use of magnetic fields for surgical devices has been proposed at several scales. Via manipulation of the magnetic field within the workspace, forces and torques can be applied to internal magnetic elements. Continuum robots have been developed with entirely soft structures embedded with magnetic micro-particles. These robots are capable of being fabricated at small- scale (less than 2 mm diameter) whilst being steered via control of electromagnetic coils or External Permanent Magnets (EPMs) [4].

Drawing inspiration from natural growth and movement strategies, vine robots possess exceptional passive shape-forming abilities, enabling them to deform around obstacles. However, an intrinsic lack of active steering limits their capacity to control their growth trajectory. This letter considers the external manipulation of such robots through the utilization of magnetically active materials embedded within the vine robot's skin. This results in a completely flexible, steerable, growing structure that can be actuated via the application of external magnetic fields and field gradients. We explore the principles of magnetically-guided vine robots and provide empirical evidence highlighting the efficacy of our proposed magnetic steering methodology. Due to the inverted internal structure, careful design of the magnetization direction of the robot has to be considered. We propose an orthogonal magnetization strategy that successfully preserves a net positive magnetization. We focus on a vine robot of 8 mm in diameter, constructed from a polyethylene substrate coated with a silicone layer embedded with magnetic micro-particles. We demonstrate the ability of our robots to navigate complex environments and steer around large obstacles in a shear free manner via the simultaneous control of both the magnetic field and the growing pressure. Finally, we demonstrate our robot by performing the selective navigation of multiple bifurcations within a bronchial tree phantom.

Wearable soft robots can be effective tools for rehabilitation due to their inherent safety and compliance. Challenges, however, exist regarding the development of suitable on-body actuation methods. Furthermore, the majority of existing soft wearable devices are not accessible and easy to use for those with physical disabilities. This paper presents the design, fabrication, and characterization of a soft robotic wrist orthosis to achieve flexion and extension for continuous passive motion therapy. First, we developed bending textile pneumatic actuators that could be mechanically programmed to conform to the target joint's anatomy when mounted on the body. The textile pneumatic actuators achieved up to 2.24 Nm of torque at 124 kP <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$a$</tex> . We then embedded the textile pneumatic actuators into a soft wrist orthosis that we designed to ensure it was easy to don/doff without assistance. To determine the operating pressures and range of motion achievable by our soft robotic wrist orthosis, we conducted a device evaluation study with three healthy individuals. Our device achieved over 100 degrees of flexion/extension assistance at operating pressures below 90 kPa. This work takes the first steps towards developing a wearable soft robotic device that can deliver passive therapy at home without the need for a physical therapist or assistant.

The majority of educational haptic devices to date are grounded to a stationary surface, limiting the concepts that can be taught. In this work, we introduce the Hand-Held Haptic Kit (H <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> Kit) — a body-grounded, kinesthetic feedback device for STEM education. We present a kinematic analysis that illustrates how the reachable workspace can differ depending on whether or not there is joint alignment between the device and the user. We then conduct a psychophysical study that shows that users’ perception of stiffness forces are not significantly impacted by joint misalignment. Lastly, we demonstrate the use of the H <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> Kit for teaching the concept of drag forces, which leverages its ungrounded nature and added sensing capabilities.

Abstract This evidence-based practice paper will describe the transformation of the hands-on learning experience for a freshman Mechanical Engineering design course at XX University. The changes were designed to cope with the challenges raised by the remote learning environment during the COVID-19 pandemic. The standard in-person version of the course includes lectures taught in traditional lecture halls, and labs, which are performed in a Design Studio filled with a variety of fabrication equipment. As the first engineering design course in the curriculum, it provides important learning experiences for the first-year mechanical engineering students. The course teaches several critical concepts, such as basic engineering graphics and CAD skills, engineering design principles, basic machine design, prototyping skills, as well as teamwork and communication skills. These learning objectives were taught in lectures but, more importantly, they were enhanced through labs, where students could complete two hands-on projects. Project #1 was a pre-defined individual project, and project #2 was an open-ended team-based project, designed to enable creativity. As project #2 was team-based, it served to promote connections among first-year students and helped them build an inclusive community. Further, the hands-on learning experience provided an opportunity for students to gain a better understanding of mechanical engineering and to build a stronger interest in their declared major. The remote teaching setting has created a significant obstacle to providing the students with a similar hands-on learning experience required to meet the course learning objectives and goals mentioned above. The lack of access to hardware materials and laboratory equipment has significantly reduced the feasibility of implementing hands-on course projects. Although students can still complete parts of the design process, including conceptual design generation and Computer-Aided-Design modeling, the lack of hands-on prototyping, analysis, and design iteration has hindered students’ mastery of important concepts usually learned through project application. Lastly, the absence of an engaging course project may also reduce students’ motivation and interest in the subject matter. To address these issues, a transformation of the hands-on learning component of the course was planned and implemented. One element of the transformation was to create hardware kits that allow students to work at home on projects similar to the in-person version of the course, and enable them to achieve the same learning objectives. One challenge was to ensure that the kit contained all necessary tools and materials needed for fabricating parts without access to lab equipment, such as laser cutters or 3D printers. Another element of the transformation was to modify the structure of both projects, in order to make the hands-on activities feasible and compatible with the hardware kits developed, while also preserving the learning objectives and course goals. Risks, such as safety, were considered and mitigated during the development of the hardware kits and project structure. In this paper, we will use students’ work, survey feedback, course evaluations, and focus group interview data to assess the success of the hands-on learning experience transformation for remote learning. We will compare data from three sources: (i) data from terms when the course was taught in the regular in-person setting, where the students have access to lab materials and equipment, (ii) previous term when the course was delivered remotely but without the new hardware kits, and (iii) data from the current remote term with the newly developed hardware kits. We will evaluate students’ project design deliverables to assess the effectiveness of achieving course learning objectives using the hardware kit. We will also investigate how the modified hands-on learning experiences have impacted students' perception on their first-year engineering experience, including any changes in their level of interest in engineering and in their sense of belonging in the mechanical engineering community. Although the transformation described in this paper was motivated by the remote teaching forced by the COVID-19 pandemic, it can also be used for design courses that are intended to be online.

Abstract This work-in-progress paper presents the transformation of a lab activity for a first-year mechanical engineering design class at xxx university. The changes were designed to cope with the challenges raised by the remote learning environment during the COVID-19 pandemic. This first-year mechanical engineering design course, traditionally taught in person, consists of both lectures and lab activities. Lectures and labs were focused on meeting course objectives such as identifying design problems, modeling a system to meet the desired needs, and introducing the design process through hands-on experience. All the knowledge learned from lectures and labs were reinforced through a robot design project. One important lab is the Force, Torque, and Power Energy (FTPE) analysis, in which students test for and understand concepts such as torque, spring constants, moments, power, and energy for motors, springs, rubber bands, etc. Proficiency in these concepts and skills are also important for their robot project. This analysis provides students with the opportunity to gain hands-on experience measuring and performing experiments that allow them to identify critical design constraints for their robots. In a traditional setting, students would utilize an on-campus design studio, and be given access to measuring and testing equipment, however, the pandemic has made it difficult to perform the lab in the original in-person method. Although a hardware kit was shipped to the students prior to the start of the term, due to budget limitations, a few lower-frequency utilized components (force spring gauges, stall torque measurement apparatuses, and high-speed motor counters) were omitted from the kit. Thus, a modified lab activity using low-cost, more easily accessible materials was needed. This paper describes the modified lab activity in comparison with the original one. Survey responses, assignment performance data, and equipment costs were gathered and assessed to determine the success of this modified lab in terms of cost, and how much the original learning objectives have been achieved.

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.

Abstract Many design optimization problems include constraints to prevent intersection of the geometric shape being optimized with other objects or with domain boundaries. When applying gradient-based optimization to such problems, the constraint function must provide an accurate representation of the domain boundary and be smooth, amenable to numerical differentiation, and fast-to-evaluate for a large number of points. We propose the use of tensor-product B-splines to construct an efficient-to-evaluate level set function that locally approximates the signed distance function for representing geometric non-interference constraints. Adapting ideas from the surface reconstruction methods, we formulate an energy minimization problem to compute the B-spline control points that define the level set function given an oriented point cloud sampled over a geometric shape. Unlike previous explicit non-interference constraint formulations, our method requires an initial setup operation, but results in a more efficient-to-evaluate and scalable representation of geometric non-interference constraints. This paper presents the results of accuracy and scaling studies performed on our formulation. We demonstrate our method by solving a medical robot design optimization problem with non-interference constraints. We achieve constraint evaluation times on the order of $$10^{-6}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mn>10</mml:mn> <mml:mrow> <mml:mo>-</mml:mo> <mml:mn>6</mml:mn> </mml:mrow> </mml:msup> </mml:math> seconds per point on a modern desktop workstation, and a maximum on-surface error of less than 1.0% of the minimum bounding box diagonal for all examples studied. Overall, our method provides an effective formulation for non-interference constraint enforcement with high computational efficiency for gradient-based design optimization problems whose solutions require at least hundreds of evaluations of constraints and their derivatives.

Continuum robots are well-suited for applications in delicate and constrained environments, such as minimally invasive surgery, due to their inherent compliance and ability to conform to highly curved paths. Yet the kinematic dissimilarity between continuum robots and conventional, off-the-shelf input devices, along with the general lack of haptic feedback available with such devices, can lead to non-intuitive control. In this work, we present Hapstick — a soft, flexible haptic joystick that uses fiber jamming to modulate its stiffness and provide feedback to users during teleoperation tasks. We characterize the performance of Hapstick, showing that the bending stiffness increases linearly with the increase in applied vacuum load. A psychophysical study is also conducted to obtain the just noticeable difference in stiffness that users can perceive using Hapstick. Lastly, we perform a study in which participants use Hapstick to teleoperate a physical tendon-driven continuum robot in a simulated colorectal cancer screening task. Users correctly identify the position and development stages of cancerous tissues in 25 out of 27 trials, illustrating the potential of jamming-based mechanisms as bidirectional interfaces capable of providing effective haptic feedback.

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) consist of a set of telescoping, pre-curved tubes, whose overall shape can be actively controlled by translating and rotating the tubes with respect to each other. The majority of CTRs to date consist of piecewise constant-curvature tubes, with a straight section followed by a single constant-curvature section. Several approaches have been proposed for CTR designs that can lead to improvements in metrics such as the workspace, orientability, dexterity, and stability. Here we propose to use CTRs with multiple constant-curvature sections. We perform two simulation studies that compare the performance of the multiple constant-curvature CTRs with standard single constant-curvature tubes. We also demonstrate how using one of the proposed multiple constant-curvature designs can enable the reduction in the number of tubes needed to achieve the same performance as a standard three-tube CTR.

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.

Any two objects in contact with each other exert a force that could be simply due to gravity or mechanical contact, such as any ubiquitous object exerting weight on a platform or the contact between two bones at our knee joints. The most ideal way of capturing these contact forces is to have a flexible force sensor which can conform well to the contact surface. Further, the sensor should be thin enough to not affect the contact physics between the two objects. In this paper, we showcase the design of such thin, flexible sticker-like force sensors dubbed as 'ForceStickers', ushering into a new era of miniaturized force sensors. ForceSticker achieves this miniaturization by creating new class of capacitive force sensors which avoid both batteries, as well as wires. The wireless and batteryless readout is enabled via hybrid analog-digital backscatter, by piggybacking analog sensor data onto a digitally identified RFID link. Hence, ForceSticker finds natural applications in space and battery-constraint in-vivo usecases, like force-sensor backed orthopaedic implants, surgical robots. Further, ForceSticker finds applications in ubiquiti-constraint scenarios. For example, these force-stickers enable cheap, digitally readable barcodes that can provide weight information, with possible usecases in warehouse integrity checks. To meet these varied application scenarios, we showcase the general framework behind design of ForceSticker. With ForceSticker framework, we design 4mm*2mm sensor prototypes, with two different polymer layers of ecoflex and neoprene rubber, having force ranges of 0-6N and 0-40N respectively, with readout errors of 0.25, 1.6 N error each (&lt;5% of max. force). Further, we stress test ForceSticker by &gt;10,000 force applications without significant error degradation. We also showcase two case-studies onto the possible applications of ForceSticker: sensing forces from a toy knee-joint model and integrity checks of warehouse packaging.