Robot Tip Research Articles

A multi-chamber soft robot for transesophageal echocardiography: continuous kinematic matching control of soft medical robots.

This research investigates designing a continuum soft robot and proposing a kinematic matching control to enable the robot to perform a specified medical task, which in this paper is the transesophageal echocardiography (TEE). A multi-chamber soft robot was designed and fabricated based on the molding of separate layers. The method of transformation matrices was used to develop the kinematic models, and a control method using Jacobian matrices was proposed to manipulate the robot. A prototype was made based on a multi-chamber multi-layer design. The system contains three segments that can be actuated independently to mimic the active bending part of the respective probe. Kinematic models were developed. Negative pressure (vacuum) was used as actuation input. An open-loop controller inspired by a redundancy resolution technique was proposed to make the soft robot tip follow the desired path, i.e.the path of the rigid ultrasound probe. It is concluded that the soft solution can perform the required task as the reachable points of the TEEtip cover the proposed robot workspace and the proposed control can be used for maneuvering in arbitrary trajectories.

ANN Enhanced Hybrid Force/Position Controller of Robot Manipulators for Fiber Placement

In practice, most industrial robot manipulators use PID (Proportional + Integral + Derivative) controllers, thanks to their simplicity and adequate performance under certain conditions. Normally, this type of controller has a good performance in tasks where the robot moves freely, performing movements without contact with its environment. However, complications arise in applications such as the AFP (Automated Fiber Placement) process, where a high degree of precision and repeatability is required in the control of parameters such as position and compression force for the production of composite parts. The control of these parameters is a major challenge in terms of quality and productivity of the final product, mainly due to the complex geometry of the part and the type of tooling with which the AFP system is equipped. In the last decades, several control system approaches have been proposed in the literature, such as classical, adaptive or sliding mode control theory based methodologies. Nevertheless, such strategies present difficulties to change their dynamics since their design consider only some set of disturbances. This article presents a novel intelligent type control algorithm based on back-propagation neural networks (BP-NNs) combined with classical PID/PI control schemes for force/position control in manipulator robots. The PID/PI controllers are responsible for the main control action, while the BP-NNs contributes with its ability to estimate and compensate online the dynamic variations of the AFP process. It is proven that the proposed control achieves both, stability in the Lyapunov sense for the desired interaction force between the end-effector and the environment, and position trajectory tracking for the robot tip in Cartesian space. The performance and efficiency of the proposed control is evaluated by numerical simulations in MATLAB-Simulink environment, obtaining as results that the errors for the desired force and the tracking of complex trajectories are reduced to a range below 5% in root mean square error (RMSE).

Model-based trajectory tracking of a compliant continuum robot.

Introduction: Compliant mechanisms, especially continuum robots, are becoming integral to advancements in minimally invasive surgery due to their ability to autonomously navigate natural pathways, significantly reducing collision severity. A major challenge lies in developing an effective control strategy to accurately reflect their behavior for enhanced operational precision. Methods: This study examines the trajectory tracking capabilities of a tendon-driven continuum robot at its tip. We introduce a novel feedforward control methodology that leverages a mathematical model based on Cosserat rod theory. To mitigate the computational challenges inherent in such models, we implement an implicit time discretization strategy. This approach simplifies the governing equations into space-domain ordinary differential equations, facilitating real-time computational efficiency. The control strategy is devised to enable the robot tip to follow a dynamically prescribed trajectory in two dimensions. Results: The efficacy of the proposed control method was validated through experimental tests on six different demand trajectories, with a motion capture system employed to assess positional accuracy. The findings indicate that the robot can track trajectories with an accuracy within 9.5%, showcasing consistent repeatability across different runs. Discussion: The results from this study mark a significant step towards establishing an efficient and precise control methodology for compliant continuum robots. The demonstrated accuracy and repeatability of the control approach significantly enhance the potential of these robots in minimally invasive surgical applications, paving the way for further research and development in this field.

Chorda Dorsalis System as a Paragon for Soft Medical Robots to Design Echocardiography Probes with a New SOM-Based Steering Control.

Continuum robots play the role of end effectors in various surgical robots and endoscopic devices. While soft continuum robots (SCRs) have proven advantages such as safety and compliance, more research and development are required to enhance their capability for specific medical scenarios. This research aims at designing a soft robot, considering the concepts of geometric and kinematic similarities. The chosen application is a semi-invasive medical application known as transesophageal echocardiography (TEE). The feasibility of fabrication of a soft endoscopic device derived from the Chorda dorsalis paragon was shown empirically by producing a three-segment pneumatic SCR. The main novelties include bioinspired design, modeling, and a navigation control strategy presented as a novel algorithm to maintain a kinematic similarity between the soft robot and the rigid counterpart. The kinematic model was derived based on the method of transformation matrices, and an algorithm based on a self-organizing map (SOM) network was developed and applied to realize kinematic similarity. The simulation results indicate that the control method forces the soft robot tip to follow the path of the rigid probe within the prescribed distance error (5 mm). The solution provides a soft robot that can surrogate and succeed the traditional rigid counterpart owing to size, workspace, and kinematics.

Semiautonomous Robotic Manipulator for Minimally Invasive Aortic Valve Replacement.

Aortic valve surgery is the preferred procedure for replacing a damaged valve with an artificial one. The ValveTech robotic platform comprises a flexible articulated manipulator and surgical interface supporting the effective delivery of an artificial valve by teleoperation and endoscopic vision. This article presents our recent work on force-perceptive, safe, semiautonomous navigation of the ValveTech platform prior to valve implantation. First, we present a force observer that transfers forces from the manipulator body and tip to a haptic interface. Second, we demonstrate how hybrid forward/inverse mechanics, together with endoscopic visual servoing, lead to autonomous valve positioning. Benchtop experiments and an artificial phantom quantify the performance of the developed robot controller and navigator. Valves can be autonomously delivered with a 2.0±0.5 mm position error and a minimal misalignment of 3.4±0.9°. The hybrid force/shape observer (FSO) algorithm was able to predict distributed external forces on the articulated manipulator body with an average error of 0.09 N. FSO can also estimate loads on the tip with an average accuracy of 3.3%. The presented system can lead to better patient care, delivery outcome, and surgeon comfort during aortic valve surgery, without requiring sensorization of the robot tip, and therefore obviating miniaturization constraints.

Structural design and simulation study of intelligent defect elimination equipment for high‐voltage transmission line pin defects

AbstractTransmission lines may suffer from pin defects, necessitating regular patrols and maintenance. The traditional maintenance approach not only involves a substantial workload and low efficiency but also poses a threat to the safety of maintenance personnel. To address the issue of pin defects in high‐voltage transmission lines, this paper introduces the design of an intelligent pin‐eliminating robot. The research focuses on two main aspects: firstly, analyzing the transmission line environment and employing Solidworks software to design the mechanical structure of the robot. Subsequently, a static stress analysis of the robot's structure is conducted to ensure the rationality of the design. The second aspect addresses the impact of the robot on the electric field distribution of the transmission line in high electric field intensity areas and whether the robot itself experiences discharge phenomena. COMSOL simulation software is utilized to globally calculate and analyze the electric field of the robot. Research results indicate that the threshold for the curvature radius of the pin‐eliminating robot's tip is 2.5mm, and values below this threshold may lead to the occurrence of discharge phenomena. The optimized pin‐eliminating robot, under normal operation, does not exhibit discharge phenomena in a 500kV strong electric field.

A Telescopic Tendon-Driven Needle Robot for Minimally Invasive Neurosurgery.

This paper presents the design, characterization, and testing of a steerable needle robot for minimally invasive neurosurgery. The robot consists of a rigid outer tube and two telescopic tendon-driven steerable tubes. Through the rotation, translation, and bending of individual tubes, this telescopic tendon-driven needle robot can perform dexterous motion and follow the path of the tip. We presented the design of the needle robot and its actuation system, modeling of the robotic kinematics, characterization of the robot motion, results of the open-loop kinematic control, and demonstration of the follow-the-leader motion. The position error of the robot tip is 0.92 mm, and follow-the-leader motion error is 1.1 mm. Due to its small footprint and unique motion ability, the robot has the potential to be manipulated inside human brain and used for minimally invasive neurosurgery.

Sliding-surface dynamic control of a continuum manipulator with large workspace

This paper presents the trajectory tracking control of a multi-section continuum and compliant manipulator with large workspace. Fluidic muscles are utilized as actuators in this manipulator and inertial sensors used to measure its shape in configuration space. The robot's large workspace signifies the effects of the inertial, gravitational, and applied external forces on the trajectory tracking control of the robot end-effector. In this study, a model-based sliding-surface controller is proposed by deriving a simplified Pseudo-Rigid Body (PRB) dynamic model, which utilizes modified constant curvature assumptions to describe the couplings between the robot sections and actuators. Simplification steps are proposed for a PRB dynamic model by eliminating negligible dynamic effects to achieve a computationally efficient implementation with real-time control performance. The unmodeled dynamics and the error of model simplifications are considered as system uncertainties and an integral sliding surface with a variable sliding gain is proposed to overcome these uncertain dynamics. The sliding gain considers changes in the upper bounds of uncertainties. The closed-loop system stability in trajectory tracking is mathematically proved based on the Lyapunov stability theorem. Experiments throughout the manipulator's large workspace in challenging configurations including sudden release of unknown loads at the robot tip also highlight the potential of our contributed controller.

Design and Experimental Validation of a 3D-Printed Embedded-Sensing Continuum Robot for Neurosurgery.

A minimally-invasive manipulator characterized by hyper-redundant kinematics and embedded sensing modules is presented in this work. The bending angles (tilt and pan) of the robot tip are controlled through tendon-driven actuation; the transmission of the actuation forces to the tip is based on a Bowden-cable solution integrating some channels for optical fibers. The viability of the real-time measurement of the feedback control variables, through optoelectronic acquisition, is evaluated for automated bending of the flexible endoscope and trajectory tracking of the tip angles. Indeed, unlike conventional catheters and cannulae adopted in neurosurgery, the proposed robot can extend the actuation and control of snake-like kinematic chains with embedded sensing solutions, enabling real-time measurement, robust and accurate control of curvature, and tip bending of continuum robots for the manipulation of cannulae and microsurgical instruments in neurosurgical procedures. A prototype of the manipulator with a length of 43 mm and a diameter of 5.5 mm has been realized via 3D printing. Moreover, a multiple regression model has been estimated through a novel experimental setup to predict the tip angles from measured outputs of the optoelectronic modules. The sensing and control performance has also been evaluated during tasks involving tip rotations.

Model-based Design of the COAST Guidewire Robot for Large Deflection.

Minimally invasive endovascular procedures involve the manual placement of a guidewire, which is made difficult by vascular tortuosity and the lack of precise tip control. Steerable guidewire systems have been developed with tendon-driven, magnetic, and concentric tube actuation strategies to enable precise tip control, however, selecting machining parameters for such robots does not have a strict procedure. In this paper, we develop a systematic design procedure for selecting the tube pairs of the COaxially Aligned STeerable (COAST) guidewire robot. This includes the introduction of a mechanical model that accounts for micromachining-induced pre-curvatures with the goal of determining design parameters that reduce combined distal tip pre-curvature and minimize abrupt changes in actuated tip position for the COAST guidewire robot through selection of the best flexural rigidity between the tube pairs. We present adjustments in the kinematics modeling of COAST robot tip bending motion, and use these to characterize the bending behavior of the COAST robot for varying geometries of the micromachined tubes, with an average RMSE value for the tip position error of 0.816 mm in the validation study.

Workspace Characterization for Hybrid Tendon and Ball Chain Continuum Robots.

Continuum robots have attracted considerable attention for applications in minimally invasive diagnostics and therapeutics over the past decade [1]. The primary reason is their ability to navigate narrow and tortuous anatomical passageways, while guaranteeing safe inter- action with the anatomy. In designing such robots, an important goal is create a robot with a workspace appropriate for the clinical task. A significant limitation of many continuum designs re- lates to the minimum radius of curvature that a particular design can achieve. While multiple bending sections can be concatenated to provide more degrees of freedom, the orientations by which a point in the workspace can be approached are often limited. To overcome this limitation, this paper investigates a hybrid design that combines the advantages of tendon- actuated [2] and magnetic ball chain robots [3] as shown in Fig. 1. In this hybrid design, a proximal tendon- actuated section positions the robot with respect to the goal tip location while a distal ball chain section orients the robot tip with respect to the goal location. This abstract describes how the hybrid kinematics can be modeled and illustrates how the hybrid design possesses a dextrous workspace of finite extent.

Fractional‐order sliding mode control for a novel magneto‐electro‐elastic microtube robot

AbstractIn this paper, a tracking controller based on a non‐integer sliding surface is proposed for a magneto‐electro‐elastic (MEE) fluid‐conveying microtube robot. The smart/adaptive MEE material enables us to control the robot with no need for external sensors and actuators. The micro‐robot lateral motion is modeled by Euler–Bernoulli beam equations. The governing equation of the robot is derived using the constitutive equations of MEE materials and Maxwell's principle followed by Hamilton's variational method. Based on the extracted dynamic model, a novel non‐integer order sliding mode controller is introduced to suppress the microtube vibration and to provide robust path following for the robot tip. This control approach is compatible with the parameter‐varying nature of the robot dynamics. Theoretical analyses, based on Lyapunov theory, are also conducted to verify the stability of the closed‐loop system. Comparative simulations are finally performed to show the efficiency of the proposed system in comparison with the conventional micro tubes made of smart materials and with an integer order sliding mode controller (SMC). The results demonstrate that the proposed robot properly meets the performance requirements in terms of vibration suppression and trajectory tracking, even in the presence of disturbances.

Adaptive Control of a Master-Slave Based Robotic Surgical System With Haptic Feedback

A master-slave (M-S) based robotic surgical system with haptic feedback is presented in this work for natural orifice transluminal endoscopic surgery (NOTES) using an in-vivo robot. A novel dual-loop control, including closed-loop inverse kinematics (CLIK) and adaptive control with optimal control parameters, is developed for the slave robot to track a random trajectory upon updating the dynamic parameters of the slave robot. The interaction between the slave robot tip position and environment is controlled by an impedance controller that prevents damage to healthy tissues. Upon tracking a given desired 3D trajectory as input for the slave robot by the human operator handling the master robot, the slave robot-tissue interaction force is sensed as haptic feedback at the master side. Lyapunov direct method based stability analysis and performance evaluations involving both simulation and experimental studies prove the efficacy of our novelly developed M-S robotic system aiming NOTES regulated by the proposed adaptive control strategy with optimized control parameters. Note to Practitioners: The M-S based robotic surgical system is developed to perform NOTES using a cable-driven in-vivo robot attached to the tip of a flexible endoscope. It performs tissue manipulation as per the direction given by the operator. The inclusion of haptic imitates the NOTES performed using the in-vivo robot as conventional surgery. The developed system includes the following aspects: a) The adaptive control scheme with optimal control parameters; b) Interaction force between the slave robot and tissue environment is controlled using impedance control and given as haptic feedback to the surgeon; c) The proposed system can be potentially utilized for actual teleoperated surgery and surgical training for NOTES.

Imitation-Based Motion Planning and Control of a Multi-Section Continuum Robot Interacting With the Environment

Recently, flexible robots are growing in importance owing to their merits over rigid robots in maneuverability and safety, which equips them to work in unstructured environments, such as occur in medical applications. However, motion planning and control of flexible manipulators is challenging due to their compliance behavior and system uncertainties. Thus, this letter presents an Imitation-based Motion Planning (IbMP) approach, along with dynamic impedance control for learning, planning, and trajectory tracking of a two-section soft continuum robot in a dynamic environment. Point-to-point motion demonstrations, including the robot's tip position and orientation are intuitively provided by a motion capture system (OptiTrack V120-trio) and a similar kinematic flexible interface. Additionally, a singularity-free dynamic model based on Lagrangian formulation and Taylor expansion series of a two-section continuum robot is derived while planning for robot motions. The simulation results show that the IbMP approach, along with the dynamic impedance control, generalizes the robot's motion by varying the initial and goal of the robot's tip pose while avoiding static and dynamic obstacles, and moving back to the desired track after disturbances. Finally, the stability and performance of the IbMP algorithm against input disturbances are assessed using a Monte Carlo approach that can guide the selection of gain values.

Optimum joint and trajectory tracking control of multi-axes space manipulator based on amnesia feedback controller

The space manipulators operate in an unstructured or unknown environment, increasing the dynamic complexity of space manipulator. Due to disturbance in manipulator base, the trajectory tracking control issue arises that cause error between reference and actual trajectory. Hence, to sort out these issues, this work presents optimum joint and trajectory tracking control of multi-axes space manipulator based on amnesia feedback controller. Firstly, the dynamic model of a 7DOF space manipulator built on Euler-Lagrange theorem, using the Jacobian matrix of individual link is designed. Later on, the Amnesia controller strategy is implemented that keeps a record of the trajectory tracking error and sends them to the robot tip. Compared to PID control scheme, the rising time, settling time, and overshoot is reduced even further when amnesia controller is used. The trajectory deviation using PID controller is 15°, while it is 3° using Amnesia controller, as expected. Hence, Amnesia controller reduces the trajectory tracking error between reference and actual trajectory of the redundant robot. The effectiveness of the proposed methodology employing a redundant 7DOF space robot has been verified. This proposed scheme can be utilized for on-orbit servicing and space debris removal through space craft.

Towards A Physics-based Model for Steerable Eversion Growing Robots.

Soft robots that grow through eversion/apical extension can effectively navigate fragile environments such as ducts and vessels inside the human body. This paper presents the physics-based model of a miniature steerable eversion growing robot. We demonstrate the robot's growing, steering, stiffening and interaction capabilities. The interaction between two robot-internal components is explored, i.e., a steerable catheter for robot tip orientation, and a growing sheath for robot elongation/retraction. The behavior of the growing robot under different inner pressures and external tip forces is investigated. Simulations are carried out within the SOFA framework. Extensive experimentation with a physical robot setup demonstrates agreement with the simulations. The comparison demonstrates a mean absolute error of 10 - 20% between simulation and experimental results for curvature values, including catheter-only experiments, sheath-only experiments and full system experiments. To our knowledge, this is the first work to explore physics-based modelling of a tendon-driven steerable eversion growing robot. While our work is motivated by early breast cancer detection through mammary duct inspection and uses our MAMMOBOT robot prototype, our approach is general and relevant to similar growing robots.

Stochastic model-based contact force estimation for concentric tube robots

This work utilizes a Wiener process to describe a fluctuating load on a Concentric tube robot (CTR) or its smooth motion through fixed obstacles leading to a kineto-static piecewise constant strain (KPCS) model. We then propose an observer based on the KPCS model, represented as a stochastic switched system, to estimate the externally applied forces by knowing the position of discrete points on the backbone. We have demonstrated that the observer describes the behavior of CTRs in unknown constraint environments and slow movement. The experiments carried out using electromagnetic sensors on the CTR prototype validate the feasibility of the proposed approach for shape and tip-force estimation. The average time required for force estimation is about 3.8, 6.2, and 20 ms per sample, respectively, when the estimated external forces are applied on a three-tube CTR’s tip point and three and fifteen equally spaced points along its length. The implementation results reveal the estimated force reduces the error of the robot tip position by half (about 1.5% of the robot length on average) compared to the known external force.

Hybrid Eye-in-Hand/Eye-to-Hand Image Based Visual Servoing for Soft Continuum Arms

Soft continuum arms (SCAs) that are controlled by visual servoing (VS) present trade-offs between the camera range and tracking accuracy. Cameras placed at a distance (eye-to-hand) can observe a larger workspace area and the SCA tip, while a camera at the end effector (eye-in-hand) can more accurately survey the target. In this letter, we present a hybrid eye-to-hand and eye-in-hand VS scheme to track a desired object in the SCA's worksapce. When the target is not in the field-of-view of the tip camera, hand-to-eye VS is implemented using a wide field-of-view camera on the soft robot's base, to servo the soft robot's tip to a feasible region where the target is expected to be seen by the tip camera. This region is estimated by solving an optimization problem that finds the best region to place the SCA assuming a constant curvature model for the SCA. When the target is seen by the tip camera, the system switches to a hand-in-eye controller that keeps the target in the desired image position of the tip camera. Experimental results on the popular <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$BR^{2}$</tex-math></inline-formula> SCA demonstrates the effectiveness of the hybrid VS scheme under practical settings that include external disturbances.

Visual servoing of continuum robots: Methods, challenges, and prospects.

Recent advancements in continuum robotics have accentuated developing efficient and stable controllers to handle shape deformation and compliance. The control of continuum robots (CRs) using physical sensors attached to the robot, particularly in confined spaces, is difficult due to their limited accuracy in three-dimensional deflections and challenging localisation. Therefore, using non-contact imaging sensors finds noticeable importance, particularly in medical scenarios. Accordingly, given the need for direct control of the robot tip and notable uncertainties in the kinematics and dynamics of CRs, many papers have focussed on the visual servoing (VS) of CRs in recent years. The significance of this research towards safe human-robot interaction has fuelled our survey on the previous methods, current challenges, and future opportunities. Beginning with actuation modalities and modelling approaches, the paper investigates VS methods in medical and non-medical scenarios. Finally, challenges and prospects of VS for CRs are discussed, followed by concluding remarks.

Fractional Control of a Lightweight Single Link Flexible Robot Robust to Strain Gauge Sensor Disturbances and Payload Changes

In this paper, a method to control one degree of freedom lightweight flexible manipulators is investigated. These robots have a single low-frequency and high amplitude vibration mode. They hold actuators with high friction, and sensors which are often strain gauges with offset and high-frequency noise. These problems reduce the motion’s performance and the precision of the robot tip positioning. Moreover, since the carried payload changes in the different tasks, that vibration frequency also changes producing underdamped or even unstable time responses of the closed-loop control system. The actuator friction effect is removed by using a robust two degrees of freedom PID control system which feeds back the actuator position. This is called the inner loop. After, an outer loop is closed that removes the link vibrations and is designed based on the combination of the singular perturbation theory and the input-state linearization technique. A new controller is proposed for this outer loop that: (1) removes the strain gauge offset effects, (2) reduces the risk of saturating the actuator due to the high-frequency noise of strain gauges and (3) achieves high robustness to a change in the payload mass. This last feature prompted us to use a fractional-order PD controller. A procedure for tuning this controller is also proposed. Simulated and experimental results are presented that show that its performance overcomes those of PD controllers, which are the controllers usually employed in the input-state linearization of second-order systems.