Hybrid Robotic System Research Articles

Design and Analysis of a Novel 2T2R Parallel Mechanism with the Closed-loop Limbs

This paper presents a novel four degrees of freedom (DOF) parallel mechanism with the closed-loop limbs, which includes two translational (2T) DOF and two rotational (2R) DOF. By connecting the proposed parallel mechanism with the guide rail in series, the 5-DOF hybrid robot system is obtained, which can be applied for the composite material tape laying in aerospace industry. The analysis in this paper mainly focuses on the parallel module of the hybrid robot system. First, the freedom of the proposed parallel mechanism is calculated based on the screw theory. Then, according to the closed-loop vector equation, the inverse kinematics and Jacobian matrix of the parallel mechanism are carried out. Next, the workspace stiffness and dexterity analysis of the parallel mechanism are investigated based on the constraint equations, static stiffness matrix and Jacobian condition number. Finally, the correctness of the inverse kinematics and the high stiffness of the parallel mechanism are verified by the kinematics and stiffness simulation analysis, which lays a foundation for the automatic composite material tape laying.

A Robotic System with EMG-Triggered Functional Eletrical Stimulation for Restoring Arm Functions in Stroke Survivors

Background Robotic systems combined with Functional Electrical Stimulation (FES) showed promising results on upper-limb motor recovery after stroke, but adequately-sized randomized controlled trials (RCTs) are still missing. Objective To evaluate whether arm training supported by RETRAINER, a passive exoskeleton integrated with electromyograph-triggered functional electrical stimulation, is superior to advanced conventional therapy (ACT) of equal intensity in the recovery of arm functions, dexterity, strength, activities of daily living, and quality of life after stroke. Methods A single-blind RCT recruiting 72 patients was conducted. Patients, randomly allocated to 2 groups, were trained for 9 weeks, 3 times per week: the experimental group performed task-oriented exercises assisted by RETRAINER for 30 minutes plus ACT (60 minutes), whereas the control group performed only ACT (90 minutes). Patients were assessed before, soon after, and 1 month after the end of the intervention. Outcome measures were as follows: Action Research Arm Test (ARAT), Motricity Index, Motor Activity Log, Box and Blocks Test (BBT), Stroke Specific Quality of Life Scale (SSQoL), and Muscle Research Council. Results All outcomes but SSQoL significantly improved over time in both groups (P < .001); a significant interaction effect in favor of the experimental group was found for ARAT and BBT. ARAT showed a between-group change of 11.5 points (P = .010) at the end of the intervention, which increased to 13.6 points 1 month after. Patients considered RETRAINER moderately usable (System Usability Score of 61.5 ± 22.8). Conclusions Hybrid robotic systems, allowing to perform personalized, intensive, and task-oriented training, with an enriched sensory feedback, was superior to ACT in improving arm functions and dexterity after stroke.

Global robust super-twisting algorithm with adaptive switching gains for a hybrid robot

To improve the robustness performance of dynamic sliding mode control to the time-varying uncertainties without the upper bound information in a hybrid robot system, a global robust super-twisting algorithm with adaptive switching gains is proposed. The main contributions are as follows: (1) for the problem that the robustness of the sliding mode control system is not guaranteed in the reaching phase, a global robust sliding surface is designed to eliminate the reaching phase of the sliding mode control; (2) for the chattering problem existing in the sliding phase of the sliding mode control system due to the conservative selection of switching gains, based on a reconstructive super-twisting sliding mode control and the equivalent principle, a fast-adaptive law is designed to effectively reduce the chattering while the global robustness is ensured. The stability of the proposed algorithm is proved by Lyapunov stability theorem. The simulation and experiment on the hybrid robot prototype system are implemented to verify the effectiveness of the proposed control method.

Soft Magnetic Tactile Skin for Continuous Force and Location Estimation Using Neural Networks

Soft tactile skins can provide an in-depth understanding of contact location and force through a soft and deformable interface. However, widespread implementation of soft robotic sensing skins remains limited due to non-scalable fabrication techniques, lack of customization, and complex integration requirements. In this work, we demonstrate magnetic composites fabricated with two different matrix materials, a silicone elastomer and urethane foam, that can be used as continuous tactile surfaces for single-point contact localization. Building upon previous work, we increased the sensing area from a 15 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> grid to a 40 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> continuous surface. Additionally, new preprocessing methods for the raw magnetic field data, in conjunction with the use of a neural network, enables rapid location and force estimation in free space. We report an average localization of 1 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> for the silicone surface and 2 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> for the urethane foam. Our approach to soft sensing skins addresses the need for tactile soft surfaces that are simple to fabricate and integrate, customizable in shape and material, and usable in both soft and hybrid robotic systems.

Kinematic and Dynamic Modelling for a Class of Hybrid Robots Composed of m Local Closed-Loop Linkages Appended to an n-Link Serial Manipulator

Recently, more and more hybrid robots have been designed to meet the increasing demand for a wide spectrum of applications. However, development of a general and systematic method for kinematic design and dynamic analysis for hybrid robots is rare. Most publications deal with the kinematic and dynamic issues for individual hybrid robots rather than any generalization. Hence, in this paper, we present a novel method for kinematic and dynamic modelling for a class of hybrid robots. First, a generic scheme for the kinematic design of a general hybrid robot mechanism is proposed. In this manner, the kinematic equation and the constraint equations for the robot class are derived in a generalized case. Second, in order to simplify the dynamic modelling and analysis of the complex hybrid robots, a Lemma about the analytical relationship among the generalized velocities of a hybrid robot system is proven in a generalized case as well. Last, examples of the kinematic and dynamic modelling of a newly designed hybrid robot are presented to demonstrate and validate the proposed method.

An Analytical and Modular Software Workbench for Solving Kinematics and Dynamics of Series-Parallel Hybrid Robots

Abstract Parallel mechanisms are increasingly being used as modular subsystem units in various robots and man-machine interfaces for their superior stiffness, payload-to-weight ratio, and dynamic properties. This leads to series-parallel hybrid robotic systems that are challenging to model and control due to the presence of various closed loops. Most model-based kinematic and dynamic modeling tools resolve loop closure constraints numerically and hence suffer from inefficiency and accuracy issues. Additionally, they do not exploit the modularity in robot design. In this paper, we present a modular and analytical approach toward kinematic and dynamic modeling of series-parallel hybrid robots. This approach has been implemented in a software framework called hybrid robot dynamics (hyrodyn) and its application is demonstrated with the help of a series-parallel hybrid humanoid robot recently developed at DFKI-RIC.

Local stability of PD controlled bipedal walking robots

We establish stability results for PD tracking control laws in bipedal walking robots. Stability of PD control laws for continuous robotic systems is an established result, and we extend this for hybrid robotic systems, an alternating sequence of continuous and discrete events. Bipedal robots have the leg-swing as the continuous event, and the foot-strike as the discrete event. In addition, bipeds largely have underactuations due to the interactions between feet and ground. For each continuous event, we establish that the convergence rate of the tracking error can be regulated via appropriate tuning of the PD gains; and for each discrete event, we establish that this convergence rate sufficiently overcomes the nonlinear impacts by assumptions on the hybrid zero dynamics. The main contributions are (1) Extension of the stability results of PD control laws for underactuated robotic systems, and (2) Exponential ultimate boundedness of hybrid periodic orbits under the assumption of exponential stability of their projections to the hybrid zero dynamics. Towards the end, we will validate these results in a 2-link bipedal walker in simulation.

Feedback Error Learning with Sliding Mode Control for Functional Electrical Stimulation: Elbow Joint Simulation

Motivation: Upper-limb motor impairment is one of the most common consequences after Stroke. Limited capability for performing reaching and grasping movements hinders the execution of most activities of daily living. Consequently, the quality lives of the affected individuals are severely compromised. Due to these facts, the recovery of the upper limb functional capabilities is currently one of the keystones of the rehabilitation therapy. Background: Researchers are developing new methods and technologies to boost the outcomes of rehabilitation therapy. A hybrid robotic system has been proposed as a promising rehabilitation technology that combines a passive device (Armeo Spring exoskeleton) to support the arm weight against gravity with a Functional Electrical Stimulation (FES) system to execute the reaching task. This system provides to patients the possibility of training specifically and intensive exercises. Objective: The main objective of this paper is to investigate the performance and robustness of a Feedback Error learning (FEL) scheme mixed with sliding mode control (SMC) to control the FES. Methods: We implemented a nonlinear model describing the muscle response to FES and the dynamic behavior of the elbow joint. Using this model we carried out a simulation study to compare four control strategies: computed torque control (CTC), sliding mode Control (SMC), and adaptive feedback control using FEL: ANN+ CTC and FEL: ANN+SMC. We tested these controllers in two different simulation conditions: In the absence and presence of fatigue. To check the performance of the controllers, we compared the root means square (RMSE) of tracking error and the Normalized RMS of muscle stimulation for various range of movement (ROM). Results: All four controllers achieved good tracking performance in the absence of perturbations. When introducing muscle fatigue, good tracking performance is given essentially by the adaptive control ANN+SMC. Conclusion: Among the proposed approaches, we conclude that the adaptive control (FEL: ANN + SMC) is the most efficient and robust controller, which has been proven by calculating RMSE.

CIGuide: in situ augmented reality laser guidance

Purpose A robotic intraoperative laser guidance system with hybrid optic-magnetic tracking for skull base surgery is presented. It provides in situ augmented reality guidance for microscopic interventions at the lateral skull base with minimal mental and workload overhead on surgeons working without a monitor and dedicated pointing tools.Methods Three components were developed: a registration tool (Rhinospider), a hybrid magneto-optic-tracked robotic feedback control scheme and a modified robotic end-effector. Rhinospider optimizes registration of patient and preoperative CT data by excluding user errors in fiducial localization with magnetic tracking. The hybrid controller uses an integrated microscope HD camera for robotic control with a guidance beam shining on a dual plate setup avoiding magnetic field distortions. A robotic needle insertion platform (iSYS Medizintechnik GmbH, Austria) was modified to position a laser beam with high precision in a surgical scene compatible to microscopic surgery.Results System accuracy was evaluated quantitatively at various target positions on a phantom. The accuracy found is 1.2 mm ± 0.5 mm. Errors are primarily due to magnetic tracking. This application accuracy seems suitable for most surgical procedures in the lateral skull base. The system was evaluated quantitatively during a mastoidectomy of an anatomic head specimen and was judged useful by the surgeon.Conclusion A hybrid robotic laser guidance system with direct visual feedback is proposed for navigated drilling and intraoperative structure localization. The system provides visual cues directly on/in the patient anatomy, reducing the standard limitations of AR visualizations like depth perception. The custom- built end-effector for the iSYS robot is transparent to using surgical microscopes and compatible with magnetic tracking. The cadaver experiment showed that guidance was accurate and that the end-effector is unobtrusive. This laser guidance has potential to aid the surgeon in finding the optimal mastoidectomy trajectory in more difficult interventions.

A Hybrid Robotic System for Arm Training of Stroke Survivors: Concept and First Evaluation.

To develop and evaluate a hybrid robotic system for arm recovery after stroke, combining ElectroMyoGraphic (EMG)-triggered functional electrical stimulation (FES) with a passive exoskeleton for upper limb suspension. The system was used in a structured exercise program resembling activities of daily life. Exercises execution was continuously controlled using angle sensor data and radio-frequency identification technology. The training program consisted of 27 sessions lasting 30 min each. Seven post-acute stroke patients were recruited from two clinical sites. The efficacy of the system was evaluated in terms of action research arm test, motricity index, motor activity log, and box & blocks tests. Furthermore, kinematics-based and EMG-based outcome measures were derived directly from data collected during training sessions. All patients showed an improvement of motor functions at the end of the training program. After training, the exercises were in most cases executed faster, smoother, and with an increased range of motion. Subjects were able to trigger FES, but in some cases, they did not maintain the voluntary effort during task execution. All subjects but one considered the system usable. The preliminary results showed that the system can be used in a clinical environment with positive effects on arm functional recovery. However, only the final results of the currently ongoing clinical trial will unveil the system's full potential. The presented hybrid robotic system is highly customizable, allows to monitor the daily performance, requires low supervision of the therapist, and might have the potential to enhance arm recovery after stroke.

Hybrid robotic system combining passive exoskeleton and functional electrical stimulation for upper limb stroke rehabilitation: Preliminary results of the retrainer multi-center randomized controlled trial

Stroke is the main cause of acquired adult disability with major impact on arm function. The combined use of Functional Electrical Stimulation (FES) and robotic technologies is strongly advocated to improve rehabilitation outcomes after stroke. We present the preliminary data of a multi-center Randomized Controlled Trial aimed at evaluating the effectiveness of this system with respect to conventional therapy for sub-acute stroke upper limb rehabilitation. The RETRAINER system consists of a lightweight and non-cumbersome passive arm exoskeleton for weight relief, a current-controlled stimulator with 2 channels of stimulation and 2 channels of EMG recordings. In this work we are presenting the preliminary results of 39 sub-acute stroke patients with a distance from the acute event between two weeks and nine months. The inclusion criteria was: age between 18 and 85 years, Motricity Index (MI) < 80%, muscular activity for arm and shoulder at least 1 Medical Research Council (MRC) with a visible contraction, no joint limitation, pain or spasticity. They were randomized in two group: 1 conventional rehabilitation methods, 2 experimental group using Retrainer System. Each participant performed 9 weeks of treatment 3 times for week. We measured MI, Action Research Arm Test (ARAT) and Motor Activity Log (MAL) at beginning (T0) and at the end of treatment (T1). Results are showed in the next Table 1 . Both groups showed statistical improvement in outcome measures. Experimental group showed a statistical better improvement regarding time and group effect.

Adaptive hybrid robotic system for rehabilitation of reaching movement after a brain injury: a usability study

BackgroundBrain injury survivors often present upper-limb motor impairment affecting the execution of functional activities such as reaching. A currently active research line seeking to maximize upper-limb motor recovery after a brain injury, deals with the combined use of functional electrical stimulation (FES) and mechanical supporting devices, in what has been previously termed hybrid robotic systems. This study evaluates from the technical and clinical perspectives the usability of an integrated hybrid robotic system for the rehabilitation of upper-limb reaching movements after a brain lesion affecting the motor function.MethodsThe presented system is comprised of four main components. The hybrid assistance is given by a passive exoskeleton to support the arm weight against gravity and a functional electrical stimulation device to assist the execution of the reaching task. The feedback error learning (FEL) controller was implemented to adjust the intensity of the electrical stimuli delivered on target muscles according to the performance of the users. This control strategy is based on a proportional-integral-derivative feedback controller and an artificial neural network as the feedforward controller. Two experiments were carried out in this evaluation. First, the technical viability and the performance of the implemented FEL controller was evaluated in healthy subjects (N = 12). Second, a small cohort of patients with a brain injury (N = 4) participated in two experimental session to evaluate the system performance. Also, the overall satisfaction and emotional response of the users after they used the system was assessed.ResultsIn the experiment with healthy subjects, a significant reduction of the tracking error was found during the execution of reaching movements. In the experiment with patients, a decreasing trend of the error trajectory was found together with an increasing trend in the task performance as the movement was repeated. Brain injury patients expressed a great acceptance in using the system as a rehabilitation tool.ConclusionsThe study demonstrates the technical feasibility of using the hybrid robotic system for reaching rehabilitation. Patients’ reports on the received intervention reveal a great satisfaction and acceptance of the hybrid robotic system.Trial registrationRetrospective trial registration in ISRCTN Register with study ID ISRCTN12843006.

Robotic Transnasal Endoscopic Skull Base Surgery: Systematic Review of the Literature and Report of a Novel Prototype for a Hybrid System (Brescia Endoscope Assistant Robotic Holder).

Although robotics has already been applied to several surgical fields, available systems are not designed for endoscopic skull base surgery (ESBS). New conception prototypes have been recently described for ESBS. The aim of this study was to provide a systematic literature review of robotics for ESBS and describe a novel prototype developed at the University of Brescia. PubMed and Scopus databases were searched using a combination of terms, including Robotics OR Robot and Surgery OR Otolaryngology OR Skull Base OR Holder. The retrieved papers were analyzed, recording the following features: interface, tools under robotic control, force feedback, safety systems, setup time, and operative time. A novel hybrid robotic system has been developed and tested in a preclinical setting at the University of Brescia, using an industrial manipulator and readily available off-the-shelf components. A total of 11 robotic prototypes for ESBS were identified. Almost all prototypes present a difficult emergency management as one of the main limits. The Brescia Endoscope Assistant Robotic holder has proven the feasibility of an intuitive robotic movement, using the surgeon's head position: a 6 degree of freedom sensor was used and 2 light sources were added to glasses that were therefore recognized by a commercially available sensor. Robotic system prototypes designed for ESBS and reported in the literature still present significant technical limitations. Hybrid robot assistance has a huge potential and might soon be feasible in ESBS.

Effect Of Ankle Plantar Flexion On ACL Strain During Landing From A Jump

Injuries to the Anterior Cruciate Ligament (ACL) are one of the most common injuries in athletic activities. Landing from a jump is one of the leading athletic activities associated with ACL injuries. Researchers have postulated that landing flat footed (hill contact) is a more detrimental landing posture to ACL health than landing on toes (or ball of foot). In this research, a novel hybrid robotic system utilizing cadaveric legs (six inches above the knee joint to the toes) was designed to simulate lower extremity biomechanics. The robotic system has the ability to raise a cadaveric leg with pre-applied muscle forces and instrumented ACL to a desired height and drop it onto a force plate. Because we have full access to the foot and ankle joint, tests were performed to determine the impact of flat footed versus plantar flexed landing at various hip and knee flexion angles. PURPOSE: To compare the strain of the ACL during a one inch jump landing with foot in a toe down, plantar flexion position verses flat footed, with foot parallel to contact surface. METHODS: Four cadaveric knees were tested using a hybrid biomechanical device designed to simulate athletic activities such as landing from a jump, or a plant and cut movement. The cadaveric knees were attached to the device by insertion of a threaded rod implanted into the femur. Quadriceps and Hamstring (Q/H) forces were applied by the use of linear pull cables attached to the associated muscle group. Hip flexion angle was controlled allowing comparison of ACL strain at different degrees of hip flexion during flat-footed and plantar flexed landing scenarios. ACL deformation, Ground Reaction Force (GRF), Q/H forces, and Hip Flexion/Extension were measured across all tests. Data was post-processed using MATLAB to find maximum GRF, ACL deformation during impact, and associated muscle forces. T tests were performed comparing ACL strain of flat-footed vs. plantar-flexed landings. RESULTS: ACL strain of flat footed landings at all hip flexion angles were significantly higher than the plantar flexed tests (p = 0.0019). CONCLUSION: Our results indicate that landing from a jump with the foot plantar flexed lowers the strain on the ACL compared to a flat footed jump landing. The main reason for this could be the shock absorbing role of the ankle and foot ligaments during the plantar flexed landings.

Hybrid robotic systems for upper limb rehabilitation after stroke: A review

In recent years the combined use of functional electrical stimulation (FES) and robotic devices, called hybrid robotic rehabilitation systems, has emerged as a promising approach for rehabilitation of lower and upper limb motor functions. This paper presents a review of the state of the art of current hybrid robotic solutions for upper limb rehabilitation after stroke. For this aim, studies have been selected through a search using web databases: IEEE-Xplore, Scopus and PubMed. A total of 10 different hybrid robotic systems were identified, and they are presented in this paper. Selected systems are critically compared considering their technological components and aspects that form part of the hybrid robotic solution, the proposed control strategies that have been implemented, as well as the current technological challenges in this topic. Additionally, we will present and discuss the corresponding evidences on the effectiveness of these hybrid robotic therapies. The review also discusses the future trends in this field.

Combining a hybrid robotic system with a bain-machine interface for the rehabilitation of reaching movements: A case study with a stroke patient.

Reaching and grasping are two of the most affected functions after stroke. Hybrid rehabilitation systems combining Functional Electrical Stimulation with Robotic devices have been proposed in the literature to improve rehabilitation outcomes. In this work, we present the combined use of a hybrid robotic system with an EEG-based Brain-Machine Interface to detect the user's movement intentions to trigger the assistance. The platform has been tested in a single session with a stroke patient. The results show how the patient could successfully interact with the BMI and command the assistance of the hybrid system with low latencies. Also, the Feedback Error Learning controller implemented in this system could adjust the required FES intensity to perform the task.

Feedback Error Learning Controller for Functional Electrical Stimulation Assistance in a Hybrid Robotic System for Reaching Rehabilitation.

Hybrid robotic systems represent a novel research field, where functional electrical stimulation (FES) is combined with a robotic device for rehabilitation of motor impairment. Under this approach, the design of robust FES controllers still remains an open challenge. In this work, we aimed at developing a learning FES controller to assist in the performance of reaching movements in a simple hybrid robotic system setting. We implemented a Feedback Error Learning (FEL) control strategy consisting of a feedback PID controller and a feedforward controller based on a neural network. A passive exoskeleton complemented the FES controller by compensating the effects of gravity. We carried out experiments with healthy subjects to validate the performance of the system. Results show that the FEL control strategy is able to adjust the FES intensity to track the desired trajectory accurately without the need of a previous mathematical model.

Design and Analysis of a Cable-Driven Articulated Rehabilitation System for Gait Training

Assisted motor therapies play a critical role in enhancing functional musculoskeletal recovery and neurological rehabilitation. Our long-term goal is to assist and automate the performance of repetitive motor-therapy of the human lower limbs. Hence, in this paper, we examine the viability of a light-weight and reconfigurable hybrid (articulated-multibody and cable) robotic system for assisting lower-extremity rehabilitation and analyze its performance. A hybrid cable-actuated articulated-multibody system is formed when multiple cables are attached from a ground-frame to various locations on an articulated-linkage-based orthosis. Our efforts initially focus on developing an analysis and simulation framework for the kinematics and dynamics of the cable-driven lower limb orthosis. A Monte Carlo approach is employed to select configuration parameters including cuff sizes, cuff locations, and the position of fixed winches. The desired motions for the rehabilitative exercises are prescribed based upon motion patterns from a normative subject cohort. We examine the viability of using two controllers—a joint-space feedback-linearized PD controller and a task-space force-control strategy—to realize trajectory- and path-tracking of the desired motions within a simulation environment. In particular, we examine performance in terms of (i) coordinated control of the redundant system; (ii) reducing internal stresses within the lower-extremity joints; and (iii) continued satisfaction of the unilateral cable-tension constraints throughout the workspace.

Electric Field Control of Bacteria-Powered Microrobots Using a Static Obstacle Avoidance Algorithm

A bacteria-powered microrobot (BPM) is a hybrid robotic system consisting of an SU-8 microstructure with active surfaces or bacterial carpets, in which massive arrays of biomolecular flagellar motors work cooperatively. This paper suggests an obstacle-avoidance method based on a BPM's response to electric fields. The negatively charged bacteria enable the BPM to follow electric fields. In our previous demonstration of the single BPM controllability, we observed a vast change in the control dynamics when obstructions distorted the applied electric field and affected BPM steering and control. In this paper, we demonstrate an obstacle avoidance method that takes the electric field distortion into account to navigate a BPM through multiple static obstacles in real time. We used an artificial potential field and configuration space in our algorithm to generate an objective function for the electric field distortion and collision around/with obstacles, respectively. In addition, finite-element modeling through COMSOL Multiphysics engineering software was used to simulate charged-particle trajectories in a distorted electric field. Finally, we describe the feasibility of our proposed obstacle avoidance approach through experiments and compared these data with simulation results.

Control of a hybrid robotic system for computer-assisted interventions in dynamic environments.

Minimally invasive surgery is becoming the standard treatment of care for a variety of procedures. Surgeons need to display a high level of proficiency to overcome the challenges imposed by the minimal access. Especially when operating on a dynamic organ, it becomes very difficult to align instruments reliably and precisely. In this paper, a hybrid rigid/continuum robotic system and a dedicated robotic control approach are proposed to assist the surgeon performing complex surgical gestures in a dynamic environment. The proposed robotic system consists of a rigid robot arm on top of which a continuum robot is mounted in series. The continuum robot is locally actuated with McKibben muscles. A control scheme based on quadratic programming framework is adopted. It is shown that the framework allows enforcing a set of constraints on the pose of the tip, as well as of the instrument shaft, which is commanded to slide in and out through the entry point. Through simulation and experiments, it is shown how the robot tool tip is able to follow sinusoidal trajectories of 0.37 and 2Hz, while maintaining the instrument shaft pivoting along the entry point. The positioning and tracking accuracy of such system are shown to lie below 4.7mm in position and [Formula: see text] in angle. The results suggest a good potential for applying the proposed technology to assist the surgeon during complex robot-assisted interventions. It is also illustrated that even when using flexible hence relatively safe end-effectors, it is possible to reach acceptable tracking behaviour at relatively high frequencies.