Catheters and guidewires are increasingly used to navigate tortuous paths offering minimal invasive access to deeply seated locations in the body. Steering these instruments is highly challenging among others due to poor awareness of the configuration such instrument takes on in the body. To address this difficulty research in physical intelligence has been conducted. The aim is to delegate part of the control problem locally and have the instrument determine itself how to effectively interact with its physical environment. To enable such smart behaviour this paper presents a compact FBG (fiber Bragg grating) based drive system for controlling the bending of the distal tip of a steerable catheter. The design process establishes key constraints for selecting an appropriate FBG fiber based on the selected backbone’s characteristics. Force estimation is done using the strain measured via the fiber with a root mean square error (RMSE) of 0.05 N which is then used to train a Long Short-Term Memory (LSTM) network to detect possible contact with the surroundings using the force prediction of the trained model. The trained model was able to predict the force with an RMSE of 0.012 N in a non-contact scenario. The results indicate that the proposed system incorporating FBG sensing, pneumatic artificial muscle (PAM) actuation, and LSTM based contact detection offers a promising pathway for more precise and versatile catheter manipulation in minimally invasive interventions.

Spinal fusion surgery requires highly accurate implantation of pedicle screw implants, which must be conducted in critical proximity to vital structures with a limited view of the anatomy. Robotic surgery systems have been proposed to improve placement accuracy. Despite remarkable advances, current robotic systems still lack advanced mechanisms for continuous updating of surgical plans during procedures, which hinders attaining higher levels of robotic autonomy. These systems adhere to conventional rigid registration concepts, relying on the alignment of preoperative planning to the intraoperative anatomy. In this paper, we propose a safe deep reinforcement learning (DRL) planning approach (SafeRPlan) for robotic spine surgery that leverages intraoperative observation for continuous path planning of pedicle screw placement. The main contributions of our method are (1) the capability to ensure safe actions by introducing an uncertainty-aware distance-based safety filter; (2) the ability to compensate for incomplete intraoperative anatomical information, by encoding a-priori knowledge of anatomical structures with neural networks pre-trained on pre-operative images; and (3) the capability to generalize over unseen observation noise thanks to the novel domain randomization techniques. Planning quality was assessed by quantitative comparison with the baseline approaches, gold standard (GS) and qualitative evaluation by expert surgeons. In experiments with human model datasets, our approach was capable of achieving over 5% higher safety rates compared to baseline approaches, even under realistic observation noise. To the best of our knowledge, SafeRPlan is the first safety-aware DRL planning approach specifically designed for robotic spine surgery.

Endovascular intervention is a minimally invasive method for treating cardiovascular diseases. Although fluoroscopy, known for real-time catheter visualization, is commonly used, it exposes patients and physicians to ionizing radiation and lacks depth perception due to its 2D nature. To address these limitations, a study was conducted using teleoperation and 3D visualization techniques. This in-vitro study involved the use of a robotic catheter system and aimed to evaluate user performance through both subjective and objective measures. The focus was on determining the most effective modes of interaction. Three interactive modes for guiding robotic catheters were compared in the study: 1) Mode GM, using a gamepad for control and a standard 2D monitor for visual feedback; 2) Mode GH, with a gamepad for control and HoloLens providing 3D visualization; and 3) Mode HH, where HoloLens serves as both control input and visualization device. Mode GH outperformed other modalities in subjective metrics, except for mental demand. It exhibited a median tracking error of 4.72 mm, a median targeting error of 1.01 mm, a median duration of 82.34 s, and a median natural logarithm of dimensionless squared jerk of 40.38 in the in-vitro study. Mode GH showed 8.5%, 4.7%, 6.5%, and 3.9% improvements over Mode GM and 1.5%, 33.6%, 34.9%, and 8.1% over Mode HH for tracking error, targeting error, duration, and dimensionless squared jerk, respectively. To sum up, the user study emphasizes the potential benefits of employing HoloLens for enhanced 3D visualization in catheterization. The user study also illustrates the advantages of using a gamepad for catheter teleoperation, including user-friendliness and passive haptic feedback, compared to HoloLens. To further gauge the potential of using a more traditional joystick as a control input device, an additional study utilizing the Haption Virtuose robot was conducted. It reveals the potential for achieving smoother trajectories, with a 38.9% reduction in total path length compared to a gamepad, potentially due to its larger range of motion and single-handed control.

In this article, a deep learning method for the shape sensing of continuum robots based on multicore fiber bragg grating (FBG) fiber is introduced. The proposed method, based on an artificial neural network (ANN), differs from traditional approaches, where accurate shape reconstruction requires a tedious characterization of many characteristic parameters. A further limitation of traditional approaches is that they require either multiple fibers, whose location relative to the centerline must be precisely known (calibrated), or a single multicore fiber whose position typically coincides with the neutral line. The proposed method addresses this limitation and, thus, allows shape sensing based on a single multicore fiber placed off-center. This helps in miniaturizing and leaves the central channel available for other purposes. The proposed approach was compared to a recent state-of-the-art model-based shape sensing approach. A two-degree-of-freedom benchtop fluidics-driven catheter system was built to validate the proposed ANN. The proposed ANN-based shape sensing approach was evaluated on a 40-mm-long steerable continuum robot in both 3-D free-space and 2-D constrained environments, yielding an average shape sensing error of 0.24 and 0.49 mm, respectively. With these results, the superiority of the proposed approach compared to the recent model-based shape sensing method was demonstrated.

Increased demand for less invasive procedures has accelerated the adoption of Intraluminal Procedures (IP) and Endovascular Interventions (EI) performed through body lumens and vessels. As navigation through lumens and vessels is quite complex, interest grows to establish autonomous navigation techniques for IP and EI for reaching the target area. Current research efforts are directed toward increasing the Level of Autonomy (LoA) during the navigation phase. One key ingredient for autonomous navigation is Motion Planning (MP) techniques. This paper provides an overview of MP techniques categorizing them based on LoA. Our analysis investigates advances for the different clinical scenarios. Through a systematic literature analysis using the PRISMA method, the study summarizes relevant works and investigates the clinical aim, LoA, adopted MP techniques, and validation types. We identify the limitations of the corresponding MP methods and provide directions to improve the robustness of the algorithms in dynamic intraluminal environments. MP for IP and EI can be classified into four subgroups: node, sampling, optimization, and learning-based techniques, with a notable rise in learning-based approaches in recent years. One of the review's contributions is the identification of the limiting factors in IP and EI robotic systems hindering higher levels of autonomous navigation. In the future, navigation is bound to become more autonomous, placing the clinician in a supervisory position to improve control precision and reduce workload.

Robotic comanipulation provides a cost-effective solution to telesurgery when remote operation is not strictly necessary. Within the field of laparoscopic surgery, the comanip-ulation scenario is only recently being exploited commercially in the form of lightweight backdrivable systems. A passive wrist backdrivable robot does not require preoperative alignment with the incision that acts as a fulcrum around which the laparoscopic instrument pivots. Moreover, backdrivable systems can be comanipulated by the user without the need for expensive force sensors. Unfortunately, most backdrivable systems only provide limited accuracy when measuring the end effector pose from their joint encoders. Accurate knowledge of the end effector pose is required to estimate the the instrument tip and fulcrum position. This work presents a robust method to improve localisation of the pose of the end effector of a backdrivable robot. The method fuses optical tracking with robot proprioception by means of an unscented Kalman filter and is robust against intermittent occlusions of the line of sight. The algorithm is experimentally validated by analyzing its initialization behavior and accuracy when estimating the instrument tip and fulcrum position. An accuracy of$1.58\pm 0.157$mm and$0.699\pm 0.389$mm is achieved when estimating the instrument tip and fulcrum position respectively, which makes the algorithm suitable for advanced guidance schemes in comanipulation robotic surgery.

Force sensing is highly desirable in minimally invasive medical applications, since this feature shows great potential for reducing tissue damage and enhancing manipulation safety. However, embedding force sensors in medical devices is challenging and costly. This article explores the possibility to use shape sensing as a measure to extract force information. In this work, a model-based approach that allows simultaneous shape and force sensing is proposed. Shape information is reconstructed employing a multicore fiber with fiber Bragg grating sensors spaced over the fiber length. This fiber is capable of distributed 3D shape sensing. It is shown how by making use of extended Kalman filter and a mechanics model of the flexible instrument, it becomes possible to estimate both the magnitudes and locations of externally applied forces. Experiments were carried out to validate the proposed method for both one and two external forces applied at arbitrary locations in different directions on a flexible instrument. Results show that one-directional force magnitude and location can be estimated with an average error of 23.08 mN (15.39%) and 11.06 mm (6.51%), respectively. For two-directional forces, results of the load near the base show an average error of 52.01 mN (30.59%) for the magnitude and 29.24 mm (17.20%) for the location. For the load applied simultaneously near the tip, the mean magnitude error is 16.79 mN (11.19%) and the average location error is 10.18 mm (5.99%). The force sensing algorithm can run in real time with an approximate frequency of 59 Hz. In these experiments, it can be observed that the force-sensing accuracy, which depends on the sensitivity of the shape of flexible instruments with respect to the external force, can vary drastically in function of the force application point and force direction.

Fetoscopy is a technically challenging surgery, due to the dynamic environment and low diameter endoscopes often resulting in a limited field of view. In this paper, we report on the design and operation of a robotic multimodal endoscope with optical ultrasound and white light stereo camera. The manufacture and control of the endoscope is presented, along with large area (80 mm ×80 mm) surface visualisations of a placenta phantom using the optical ultrasound sensor. The repeatability of the surface visualisations was found to be 0. 446 ± 0.139 mm and 0. 267 ± 0.017 mm for a raster and spiral scan, respectively.

During robot-assisted surgery, a Remote Center of Motion (RCM) is often implemented to constrain instrument motion through and about a specific point in space. Aligning and re-positioning this point during surgery is not trivial, as this is a defined, yet often non-visualised, point in space. When misaligned with the patient surrounding anatomy is excessively strained, potentially causing post-operative complications. Not being able to safely re-position the RCM for these purposes limits the use of surgical robotics. This work introduces a general approach relying on anatomy-based haptic fixtures to simplify and improve RCM positioning during robot-assisted surgery. The proposed approach is extended with a novel method and mechanism to mechanically implement such fixtures. This is applied for the use case of vitreoretinal surgery, for which purpose a dedicated robotic setup and fixture mechanism was developed. These were used to conduct an initial experimental validation, during which the feasibility of both a virtual and mechanical implementation is reviewed. Initial outcomes suggest that both implementations are feasible. With the currently used impedance-type system, the mechanical implementation is shown to offer at least one order of magnitude stiffness increase when compared to an equivalent virtual implementation.

Minimally invasive surgery is now a well established field in surgery but continuous efforts are made to reduce invasiveness even further. This paper proposes a novel concept of small-diameter multi-arm robot for SinglePort Access Surgery. The concept introduces a combination of backbone and actuation principles in a macro-micro fashion to achieve an excellent decoupling of the triangulation platform (macro) and of the end-effectors (micro). Concentric tube robots are used for the triangulation platform, while compliant fluidic-actuated bending segments are used as end-effectors. The fluidic actuation is advantageous as it minimally interferes with the triangulation platform. The triangulation platform on the other hand provides a stable base for the end-effectors such that large distal actuation bandwidth can be achieved. A specific embodiment for Spina Bifida repair is developed and proposed. The surgical and technical requirements as well as the mechanical design are presented in details. A first prototype is built and characterization experiments are conducted to evaluate its performance.

At the moment, surgeons struggle curing a widespread eye disease known as retinal vein occlusion where clots obstruct the retinal vessels. Latter vascular disorder involves black spots in people's eyesight and lead eventually to blindness. A recent promising treatment consists in flushing a thrombolytic agent inside the clotted retinal vessels. The surgery implies puncturing vessels ranging from 50 to 400 microns diameter on the backside of the eye, namely the retina. Latest research succeeded in tackling several challenges around this operation: the surgeon's hand tremor and the high precision required amongst other requirements. Despite several breakthroughs, the surgeon only relies on a microscope to perform the surgery through the patient eye's lens, giving poor depth perception to properly puncture the retinal vessels. This way, the surgeon is most likely to pierce through the vessel and inject the thrombolytic drug under the retina, which would endanger the person's eyesight. In this paper, we investigate the use of a novel bio-impedance sensor developed for eye surgery. Together with this new sensor, a detection algorithm has been developed to detect the puncture and double puncture events to give a feedback to the operator of the system. As far as we are aware of, such technology doesn't exist yet in eye surgery to tackle the depth perception question. This paper aims at demonstrating the benefits of this technology.

Retinal Vein Occlusion is a common retinal vascular disorder which can cause severe loss of vision. Retinal vein cannulation followed by injection of an anti-coagulant into the affected vein is a promising treatment. However, given the scale and fragility of the surgical workfield, this procedure is considered too high-risk to perform manually. A first successful robot-assisted procedure has been demonstrated. Even though successful, the procedure remains extremely challenging. This paper aims at providing a solution for the limited perception of instrument-tissue interaction forces as well as depth estimation during retinal vein cannulation. The development of a novel combined force and distance sensing cannulation needle relying on Fiber Bragg grating (FBG) and Optical Coherence Tomography (OCT) A-scan technology is reported. The design, the manufacturing process, the calibration method, and the experimental characterization of the produced sensor are discussed. The functionality of the combined sensing modalities and the real-time distance estimation algorithm are validated respectively on in-vitro and ex-vivo models.

In collaborative human-robot navigation such as when driving semi-autonomous robotic wheelchairs, intuitive control of the mobile robot is only possible if the robot understands its user. This becomes especially important as users present varying levels of abilities and heterogeneous driving styles. Furthermore, the robot needs to consider the inherent uncertainty on its navigation task because the user may not be able to communicate his or her plans explicitly. In order to address these requirements, we have adopted a probabilistic framework to recognise navigation plans. A key component in this framework is a personalised driver model, which captures how a particular user transforms his or her mental navigation plan into inputs to the robot. In this work, we evaluate the use of Gaussian Processes to implement and calibrate this probabilistic, user-specific driver model, and this for use with haptic joysticks. Furthermore, special care was taken to obtain fast online evaluation of this user model through sparse approximation and parallel computation on a GPU. This resulted in an achievable user model evaluation frequency of 40 Hz, which is far above the navigation assistance frequency we aimed for, i.e. 5 Hz. We illustrate the validity of the approach by recognising the navigation plans of a spastic wheelchair user.

Real-time tool segmentation from endoscopic videos is an essential part of many computer-assisted robotic surgical systems and of critical importance in robotic surgical data science. We propose two novel deep learning architectures for automatic segmentation of non-rigid surgical instruments. Both methods take advantage of automated deep-learning-based multi-scale feature extraction while trying to maintain an accurate segmentation quality at all resolutions. The two proposed methods encode the multi-scale constraint inside the network architecture. The first proposed architecture enforces it by cascaded aggregation of predictions and the second proposed network does it by means of a holistically-nested architecture where the loss at each scale is taken into account for the optimization process. As the proposed methods are for real-time semantic labeling, both present a reduced number of parameters. We propose the use of parametric rectified linear units for semantic labeling in these small architectures to increase the regularization of the network while maintaining the segmentation accuracy. We compare the proposed architectures against state-of-the-art fully convolutional networks. We validate our methods using existing benchmark datasets, including ex vivo cases with phantom tissue and different robotic surgical instruments present in the scene. Our results show a statistically significant improved Dice Similarity Coefficient over previous instrument segmentation methods. We analyze our design choices and discuss the key drivers for improving accuracy.

Surgical interventions are increasingly executed minimal invasively. Surgeons insert instruments through tiny incisions in the body and pivot slender instruments to treat organs or tissue below the surface. While a blessing for patients, surgeons need to pay extra attention to overcome the fulcrum effect, reduced haptic feedback and deal with lost hand-eye coordination. The mental load makes it difficult to pay sufficient attention to the forces that are exerted on the body wall. In delicate procedures such as fetal surgery, this might be problematic as irreparable damage could cause premature delivery. As a first attempt to quantify the interaction forces applied on the patient's body wall, a novel 6 degrees of freedom force sensor was developed for an ex-vivo set up. The performance of the sensor was characterised. User experiments were conducted by 3 clinicians on a set up simulating a fetal surgical intervention. During these simulated interventions, the interaction forces were recorded and analysed when a normal instrument was employed. These results were compared with a session where a flexible instrument under haptic guidance was used. The conducted experiments resulted in interesting insights in the interaction forces and stresses that develop during such difficult surgical intervention. The results also implicated that haptic guidance schemes and the use of flexible instruments rather than rigid ones could have a significant impact on the stresses that occur at the body wall.

Accurate and precise control of catheters inside a vasculature is a difficult yet important task. Current manual approaches require significant surgical skill. Over the years, surgeons build up a sort of mental kinematic map telling them how to handle the catheter in order to steer the catheter tip safely through the vessel system. The input-output behaviour of the catheter is complex and depends heavily on its configuration within and contacts with the vasculature. This paper introduces an alternative approach to control robotic catheters. The input-output behaviour or so-called differential kinematics are derived from a patient-specific vasculature model, following a minimum-energy argumentation. The validity of the proposed approach is demonstrated experimentally. Whereas the performance of model-based approaches is obviously greatly influenced by the correctness of estimated parameters, within this work we show experimentally how reasonable performance can already be achieved within the setup that was constructed. We expect that there is still ample room for improvement by, e.g., putting more sophisticated identification, modeling and collision detection schemes into place.

Lasers are being used in various surgical procedures to remove tissue or bones, to coagulate vessels or other structures. Due to difficulties in handling only a limited number of surgeons manage to display sufficient levels of precision in Minimally Invasive Surgery (MIS) procedures. Prior works on robotic laser surgery demonstrated shorter learning curves and higher ablation precision, but unfortunately ignored the fact that most clinically relevant tasks are bi-manual by nature. Surgeons are also reluctant to use current commercial surgical robotic systems for complex laser tasks, indicating that the lack of haptic feedback prevents them from efficient and safe tissue handling in preparation of laser treatment. This paper expands earlier robotic laser work towards bi-manual operation. The paper introduces a system for precisely tensioning tissue that is being targeted by the laser. An artificial test-setup that captures some essential features of bimanual laser surgery is described. Experiments have been conducted to investigate the effect of haptic feedback on ablation performance. A comparison is made of achievable levels of ablation precision when there is no haptic feedback, when there is haptic feedback and when an automatic tension control algorithm is deployed. The conducted experimental results confirm the great potential of haptic feedback and automatic tensioning systems for complex bi-manual lasering tasks.

Retinal Vein Occlusion is a common retinal vascular disorder which can cause severe loss of vision. Retinal vein cannulation and subsequent injection of anti-coagulant in the affected vein is a promising treatment. Given the scale and the fragility of retinal veins on one side and the surgeons limited positioning precision and force perception on the other side, this procedure is considered too risky to perform manually at the moment. The paper tackles the limited force perception problem. The development of a novel force sensing cannulation needle based on Fiber Bragg Gratings is reported. The design, the calibration method and the experimental characterization of the produced force sensor are discussed. The functionality of the needle is validated by measuring puncture forces during cannulations in a custom-made retina model.

A novel fluidic actuation system has been developed for in situ imaging of anatomic tissues. The actuator consists of a micromachined superelastic tool guide driven by a pair of pneumatic artificial muscles. Two additional working channels allow easy interchange of instruments or sensing equipment. This paper describes the design and construction of the actuation system. Experimental results are also reported indicating a bending repeatability of 0.1 degrees and an operational bandwidth exceeding 8Hz. To show-case the performance of the device, the actuator was loaded with an all-optical ultrasound imaging probe. First scanned images of human placental tissue surface using an all-optical ultrasound probe are presented. While a model has been developed to estimate the probe position in space as function of the input pressure, in future work, this model will be complemented with additional sensor measurements of the bending probe taking into account the hysteretic behaviour of both muscles and nitinol structure.

Advances in miniature surgical instrumentation are key to less invasive and safer medical interventions. In cardiovascular procedures interventionalists turn towards catheter-based interventions, treating patients considered unfit for classical more invasive approaches. Improvements in design and steerability of catheters could further reduce the invasiveness of these interventions. For example, by improving controllability and interaction forces with the vessels, tissue damage could be limited. Through improved steerability and coordinated control, operation times and exposure to radiation might also be reduced. Latter argument formed the original motivation for the development of teleoperated robotic catheters. Despite the large kinematic dissimilarity and thus non-trivial mapping between joystick input and catheter output motion, few investigations have been conducted to find intuitive mappings that allow straightforward catheter steering. This paper presents some recent work in this direction. Three promising mappings are proposed. The mappings were implemented and validated upon a robotic catheter moving inside an artificial aorta model. Experimental results show good steerability of the robotic catheter for all the mappings. Although superiority of one mapping with respect to the others was observed, further investigation and validation is planned. In the future, additional visual cues that increase the situational awareness of the user are expected to further simplify the steering.

This paper introduces a framework for constraint-based force/position control of robots that exhibit large nonlinear structural compliance and that undergo large deformations. Controller synthesis follows hereto the principles of the Task Frame and instantaneous Task Specification using Constraints (iTaSC) formalisms. iTaSC is found particularly suitable due to its ability to express and combine control tasks in a natural way. Control tasks can be formulated as combinations of target positions, velocities, or forces expressed in an arbitrary number and type of coordinate frames. The proposed framework is applied to a mixed mechatronic system composed of a traditional rigid-link robot whose end-effector is a continuum (flexible) link. A selection of different position/force control tasks is prepared to demonstrate the validity and general nature of the proposed framework.

Retinal surgery is one of the most challenging types of surgery because of the scale and the fragility of the human eye anatomy. The surgeon suffers from limited positioning accuracy, tremor and poor force feedback directly affecting the quality of the surgical procedures. To tackle these issues, we developed a teleoperation system to assist surgeons during retinal surgery. The system offers features like motion scaling, tremor compensation and scaled force feedback. This paper reports on the design of the slave and the master.

This paper presents a mathematical formulation for calculation of the compliance of continuum type of robots. The mathematical model of the continuum robot is built following the Cosserat rod theory and focuses on a single section Cosserat rod under arbitrary loading. The compliance of the robot is described as a set of ordinary differential equations with split boundary conditions. This new set of compliance equations is directly coupled to the solution of the forward kinematics of the robot. After solving the forward kinematics problem, these solutions can be directly used to compute the compliance. A particular class of continuum robots in which the compliance of the robot can be formulated as an initial value problem and solved in a single numerical integration is discussed. The paper provides experimental validation of the proposed method.

Navigating an electrical wheelchair can be very challenging due to its large size and limited maneuverability. Additionally, target users often suffer from cognitive or physical disabilities, which interfere with safe navigation. Therefore, a robotic wheelchair that helps to drive can prove invaluable. Such a wheelchair shares the control with its human operator. Typically, robots excel in fine-motion control whereas users want to remain in charge. Hence, the robot should focus its help locally and let the user decide about global behavior. Further, an effective robot should understand the navigation plans of its user. It needs to consider the user's abilities to avoid frustrating the user with wrong assistance. In order to address these requirements, we propose a probabilistic framework to recognize local navigation plans in a user-specific way. The framework infers navigation plans online and provides a method to calibrate all model parameters from real driving data. It fuses past local information with a user-specific model to reason about how and where the user intends to navigate. We illustrate the validity of our approach by recognizing the local navigation plans of a spastic user driving in a daily environment.

Retinal Vein Occlusion (RVO) is a common retinal vascular disorder which may cause severe loss of vision. Retinal cannulation appears to be the most effective treatment, but given the small diameter of a retinal vein, it is too difficult and risky for a surgeon to perform this procedure manually. This work reports on the development of an innovative robotic manipulator to assist vitreoretinal surgeons during this procedure using a co-manipulation control strategy. The robotic manipulator features a new Remote-Center-of-Motion mechanism with four degrees of freedom. This mechanism is particularly interesting for applications in minimally invasive surgery where an instrument needs to be manoeuvred in a highly confined space around a fixed incision point. The developed manipulator is shown to be a great asset in improving the quality of retinal cannulations compared to the manual procedure. This is shown by cannulation experiments performed on a custom made eye model and an injectable retina model that effectively simulate real retinal cannulations.

This article introduces a set of novel haptic guidance algorithms intended to provide intuitive and reliable assistance for electric wheelchair navigation through narrow or crowded spaces. The proposed schemes take hereto the non-holonomic nature and a detailed geometry of the wheelchair into consideration. The methods encode the environment as a set of collision-free circular paths and, making use of a model-free impedance controller, `haptically' guide the user along collision-free paths or away from obstructed paths or paths that simply do not coincide with the motion intended by the user. The haptic feedback plays a central role as it establishes a fast bilateral communication channel between user and wheelchair controller and allows a direct negotiation about wheelchair motion. If found unsatisfactory, suggested trajectories can always be overruled by the user. Relying on inputs from user modeling and intention recognition schemes, the system can reduce forces needed to move along intended directions, thereby avoiding unnecessary fatigue of the user. A commercial powered wheelchair was upgraded and feasability tests were conducted to validate the proposed methods. The potential of the proposed approaches was hereby demonstrated.

Minimally invasive endovascular procedures including robotically assisted intervention require effective intraoperative guidance. This is mainly achieved through intraoperative imaging such as fluoroscopy. Concerns over excessive x-ray radiation and nephrotoxicity due to repeated injection of contrast agents have motivated the development of effective catheter navigation schemes based on limited imaging data. This paper presents a catheter navigation technique based on probabilistic fusion of in situ real-time electromagnetic tracking with physically-based simulation of the mechanical characteristics of the catheter. A catheter with multiple electromagnetic sensors placed along its length has been developed. The sensor data and the catheter insertion-length are used as the boundary condition for determining the shape and position of the catheter within the vasculature. A probabilistic framework based on a Kalman Filter is used to combine the information from the catheter motion algorithm and the electromagnetic tracking data. This provides continuous visualization of the catheter within the lumen without the need of continuous fluoroscopy and contrast injection. The proposed approach has been validated with detailed in vitro experiments demonstrating the potential clinical application of the technique.

This paper analyses and compares two passivity-based approaches that allow to include a-priori knowledge on the dynamic range of the human operator and/or the environment. This can lead to less conservative teleoperation systems compared to systems designed to be purely passive or absolutely stable. The first approach under investigation is a method where the absolute stability is analysed of a teleoperation system augmented with shunt impedances in series and/or parallel with the teleoperation system. It is shown that the traditional interpretation of the use of shunt impedances is not valid and a more accurate description of how to use this method is presented. The second approach under investigation is the bounded environment (operator) method. It is shown that the original idea to restrict the analysis to the so-called worst-case scenarios of a pure mass and a pure stiffness as environment can be too simplistic. Illustrative examples with mass-spring-damper systems fixed to the ground and floating objects as environments are made to demonstrate this in detail. In conclusion, this paper shows that embedding environment knowledge into the controller analysis/design is not straightforward and further research should be dedicated to determine which bounds should be used to obtain practically stable systems for different applications.

In this paper, the Bounded Environment Passivity method is applied to a 3-channel controller. This method enables the design of teleoperation controllers that show passive behaviour for interactions with a bounded range of environments.The resulting tuning guidelines, derived analytically, provide interesting tuning flexibility, which allows to focus on different aspects of transparency. As telesurgery is the motivation behind this work, the focus lies on correctly reflecting the stiffness properties of the environment. A comparison between the transparency and stability properties of this 3-channel controller and the same properties of the Position-Force controller demonstrates the interesting properties o fthe 3-channel controller. The theoretical results are verified experimentally on a 1 d.o.f. master-slave setup.

This paper derives analytic guidelines to tune the popular Position-Force bilateral controller and improve its performance by incorporating available knowledge on the bounds of the environment impedance. The proposed guidelines can prove especially useful in the domain of telesurgery where a need exists for well-understood bilateral teleoperation controllers, that show good performance and where many tasks can be characterized by restricted and relatively easily definable impedance regions. This paper firstly analyses the two-port passivity and absolute stability properties of two alternatives of the Position-Force controller. The limitations on achievable performance when guaranteeing absolute stability with arbitrary environments are detailed. Next, a novel method, called Bounded Environment Passivity method is introduced. This method enables the design of teleoperation controllers that show passive behaviour for interactions with an environment that varies over a given range of impedances. A set of guidelines that allow a smarter trade-off between performance and stability follows. The theoretical results are verified experimentally on a 1-d.o.f. teleoperation setup.

This paper discusses variable-scale bilateral control for micro teleoperation. A method is proposed to synthesize robust variable-scale controllers that guarantee system stability and realize robust performance in contact with any arbitrary, but passive, operator and environment. The proposed method is based on the formulation as a robust output feedback constant scaled H∞problem. A variable scaled teleoperation system appears as a polytopic linear parameter-varying (LPV) plant, with an affine relation on the scale factors. Gain-scheduling is used to derive robust stable time-variant H∞controllers for online variable scaling. Improved controller performance is obtained through the introduction of an affine and scheduled-parameter-dependent weighting. The controller synthesis problem is formulated as a set of linear matrix inequalities (LMI’s) augmented with a nonconvex rank condition. An efficient algorithm is constructed to synthesize a set of sub-optimal controllers over the parameter space. The validity of the proposed methods are confirmed experimentally.

This paper describes the design of a new telepresence vision system developed to realize a higher immersive feeling for telemanipulation tasks. A new measure of 'permissible visual errors' was defined. Making use of this new measure, a minimal vision system is designed, containing only the strictly necessary DOF's (degrees of freedom) while keeping the vision errors below an experimentally obtained set of permissible errors. The result is a 4DOF camera system, containing two rotational joints (pan-tilt) and two prismatic joints (horizontal plane.) An evaluation of the system was done through a telemanipulation task using a unified hand/arm teleoperation testbed. It was found that during use of the vision system almost all visual errors remained within the permissible errors. The proposed vision system design framework suggests to break away from simply (and often blindly) mimicking human appearance. Although we only dealt with the vision system design, the same concept could be used when designing any other part of a robot.

This paper deals with the haptic rendering of collisions between a human operator and rigid objects in a virtual environment. The focus being on high-velocity impacts on a rigid wall. After discussing the importance of velocity measurements in contrast to force measurements, a new haptic device is introduced. The new device is capable of applying directly an 'impulse' to the operator, similar to collisions occurring in the real world. Based on a Poisson-model of the rigid virtual object, the necessary change of momentum of the operator's hand is being estimated online. A momentum wheel, under velocity-control, is engaged through an electromagnetic toothed clutch, at the estimated instant of impact. The resulting immediate change in momentum is thought to be essential for giving interactions with rigid virtual objects a realistic feel. Rather than generating so-called 'impulsive forces' with big motors, this approach relies only on small motors and is thus intrinsically safer. Experiments are performed on a one-degree of freedom setup. Conclusions are drawn and future directions of this research are sketched