This article presents an interactive control approach allowing a human user to teleoperate a robotic manipulator located nearby. With this approach, the user keeps his/her hands free, as only head movements are exploited to control the robot. The controller maps the 6 Degrees of Freedom (DoF) user's head position and orientation into the 6 DoF robot endeffector position and orientation. The robot can reach a large workspace thanks to the combination of two features. Firstly, a virtual wand between the user's head and the robot end-effector converts user's head pantilt rotations into large displacements of the robot end-effector center perpendicularly to the wand axis (2 DoF). Secondly, for the remaining 4 DoF (robot end-effector center displacement along the wand axis and robot en-effector orientation), realtime deformation of the virtual wand is triggered when the user reaches uncomfortable configurations due to his/her head workspace limitations. Additionally, the user gets, through an Augmented Reality (AR) Headset, a non-delayed visual feedback of the current virtual wand geometry and location. The paper includes a description of the setup and the proposed controller, detailing how the robot position/orientation is coupled to the user's head position/orientation. A set of elementary experiments with a constant-geometry wand is first presented, showing workspace limitations for some DoF. Then the wand reconfiguration is introduced in the experiments, leading to full control of 6 DoF manipulation tasks throughout a large workspace.

The prevailing and most effective approach to teleoperate a robotic arm involves a direct position-to-position mapping, imposing robotic end-effector movements that mirrors those of the user, Fig. 1-top. However, due to this one-to-one mapping, the robot's motions are limited by the user's capability, particularly in translation. Drawing inspiration from head pointers utilized in the 1980s, originally designed to enable drawing with limited head motions for tetraplegic individuals, we proposed a “virtual wand” mapping which could be used by participants with reduced mobility. This mapping employs a virtual rigid linkage between the hand and the robot's endeffector, Fig. 1-bottom. With this approach, rotations produce amplified translations through a lever arm, creating a “rotation-to-position” coupling and expanding the translation workspace at the expense of a reduced rotation space. In this study, we compare the virtual wand approach to the one-to-one position mapping through the realization of 6-DoF reaching tasks. Results indicate that the two different mappings perform comparably well, are equally well-received by users, and exhibit similar motor control behaviors. Nevertheless, the virtual wand mapping is anticipated to outperform in tasks characterized by large translations and minimal effector rotations, whereas direct mapping is expected to demonstrate advantages in large rotations with minimal translations. These results pave the way for new interactions and interfaces, particularly in disability assistance utilizing residual body movements (instead of hands) as control input. Leveraging body parts with substantial rotations could enable the accomplishment of tasks previously deemed infeasible with standard direct coupling interfaces.

This work investigates how arm swing movements measured by Inertial Motion Unit (IMU) sensors can be used to identify and maintain the walking state in a self-balanced lower-limb exoskeleton for medical use. When an exoskeleton is in a dynamical state during gait, short patterns in IMU signals (e.g. a braking movement) can be hard to extract. Therefore, by relying on a threshold-based classifier constructed upon descriptive features of actively maintained arm swing movements, it is possible to build a gait termination detection method in which the transition between the walking and standstill states occurs whenever arm movements cease, and the corresponding patterns in the IMU signals disappear. Analysis of arm IMU signals were used to identify three amplitude and coordination-based features for the classification architecture. An online implementation of this novel detection interface for maintaining the walking state was validated with 11 unimpaired participants using the Atalante exoskeleton, leading to high accuracy with less than 2% of false negatives when the arms were swinging at a high amplitude, and less than 15% when they were swinging at a medium amplitude.

One of the major functions brought by robots in Minimally Invasive Surgery is endoscope holding. This consists, for the user, in placing the camera at a desired location which the robot will maintain still once he/she releases it. This behavior is usually achieved with rigid position servoing, leading to possibly high forces generated and safety issues. Model-based weight compensation is an alternative solution. However, endoscopic cameras' weight is difficult to model as their gravity parameters can change during the same surgery. In this paper, an algorithm is presented as an option to cope with this variability in the gravity model without using rigid position servoing. The surgeon first positions the camera in a comanipulation mode (gravity compensation). When he/she releases the camera, if the gravity model is not accurate, the endoscope presents a drift. In this case, a controller brings the endoscope back to its release position by combining low gain position control and model adaptation. Once stabilized, the system is switched back to a zero-stiffness mode. Two in-vitro experiments were performed in which a user manipulates an endoscope whose configuration of mass is changed. In one case, the mass in the gravity model was set to half of the actual one. In the second case, a variable weight was attached to the endoscope. The algorithm successfully updated the model for each experiment reducing position errors by 95% and 57%, respectively.

Many human-robot collaboration scenarios can be seen as a redundant leader-follower setup where the human (i.e., the leader) can potentially perform the task without the assistance of the robot (i.e., the follower). Thus, the goal of the collaboration, beside stable execution of the task, is to reduce the human cost; e.g., ergonomic, or cognitive cost. Such system redundancies (where the same task be achieved in different manner) can also be exploited as a communication channel for the human to convey his/her intention to the robot; since it is essential for the overall performance (both execution and assistance) that the follower recognizes the intended task in an online fashion. Having an estimation for the intended task, the robot can assist the human by reducing the human cost over the task null-space; i.e., the null-space which arises from the overall system redundancies with respect to the intended task. With the prospective of supernumerary and prosthetic robots, in this work, we primarily focus on serial manipulation in which the proximal/distal part of the kinematic chain is controlled by the leader/follower respectively. By exploiting kinematic redundancies for intention-recognition and cost-minimization, our proposed control strategy (for the follower) ensures assistance under stable execution of the task. Our results (simulations and preliminary experimentation) show the efficacy of our method in providing a seamless robotic assistance (i.e., improving human posture) toward human intended tasks (i.e., reaching motions) for wearable robotics.

When the arm prosthesis worn by an amputated Human being is not adequately configured with respect to the end-effector task, body compensations are often observed. Namely, to compensate for a wrong joint positioning on the robotic distal side, a subject trying to reach a desired position/orientation of his/her hand mobilizes his/her proximal joints, thus exploiting the redundancy of the human+robot kinematic chain.In this paper, we explore the possibility of exploiting this well-known behavior to reverse the causality: if we observe the posture of an amputated subject wearing a prosthesis during a hand positioning task, to what extent can we infer the positioning error of the prosthesis?To answer this question, we make the assumption that the adequate, or natural posture for a given task is one that optimizes a postural score. The proposed approach then consists in i) measuring the joint posture of the subject fitted with the prosthesis; ii) search for an alternative posture that optimizes a postural score within the null space of the human+robot kinematic chain and iii) compute the position error for the robot joints between the initial and the optimized posture.An experimental evaluation is provided with non amputated subjects who emulate erratic positioning of their distal joints during hand positioning tasks. Results show that joint errors are estimated with a precision that seems compatible with the implementation of a real time control algorithm.

Bedside robotic endoscopes render surgeons autonomous from assistants, potentially improving surgical outcome and decreasing costs. Why then have they not been widely adopted? We take a step back and first characterize classic (non-robotic) endoscope use through observations, literature and a domain expert interview. We review the literature on bedside robotic endoscopes and find that existing controls, individually, do not have the power to support both intended and appropriated endoscope uses. We thus explore combining controls to support this diversity of uses. Through an iterative cycle, we design and implement a multimodal and mixed-initiative technique that combines two user controls and one system control. Our evaluations confirm that individual controls do not satisfy the diversity of endoscope uses, and also that our technique indeed does so. Our work highlights the relevance of HCI research in the medical domain through robotic systems.

Surgery may involve precise instrument tip positioning in a minimally invasive way. During these operations, the instrument is inserted in the body through an orifice. The movements of the instrument are constrained by interaction forces arising at the orifice level. The physical constraints may drastically vary depending on the patient’s anatomy. This introduces uncertainties that challenge the positioning task for a robot. Indeed, it raises an antagonism: On one side, the required precision appeals for a rigid behavior. On the other side, forces applied at the entry point should be limited, which requires softness. In this paper we choose to minimize forces at the orifice by using a passive ball joint wrist to manipulate the instrument. From a control perspective, this leads to consider the task as a 3 DOF wrist center positioning problem, whose softness can be achieved through conventional low impedance control. However, positioning the wrist center, even with a high static precision, does not allow to achieve a high precision of the instrument tip positioning when the orifice behavior is not known. To cope with this problem, we implement a controller that servos the tip position by commanding the wrist position. In order to deal with uncertainties, we exploit an adaptive control scheme that identifies in real-time the unknown mapping between the wrist velocity and the tip velocity. Both simulations and in vitro experimental results show the efficiency of the control law.

Beyond the ultimate goal of prosthetics, repairing all the capabilities of amputees, the development line of upper-limb prostheses control mainly relies on three aspects: the robustness, the intuitiveness and the reduction of mental fatigue. Many complex structures and algorithms are proposed but no one question a common open-loop nature, where the user is the one in charge of correcting errors. Yet, closing the control loop at the prosthetic level may help to improve the three main lines of research cited above. One major issue to build a closed-loop control is the definition of a reliable error signal; this paper proposes to use body compensations, naturally exhibited by prostheses users when the motion of their device is inaccurate, as such. The described control scheme measures these compensatory movements and makes the prosthesis move in order to bring back the user into an ergonomic posture. The function of the prosthesis is no longer to perform a given motion but rather to correct the posture of its user while s/he focus on performing an endpoint task. This concept was validated and compared to a standard open-loop scheme, for the control of a prosthetic wrist, with five healthy subjects completing a dedicated task with a customized transradial prosthesis. Results show that the presented closed-loop control allows for more intuitiveness and less mental burden without enhancing body compensation.

Robotic-assisted Minimally Invasive Surgery (MIS) is adopted more and more as it overcomes the shortcomings of classic MIS for surgeons while keeping the benefits of small incisions for patients. However, introducing new technology oftentimes affects the work of skilled practitioners. Our goals are to investigate the impacts of telemanipulated surgical robots on the work practices of surgical teams and to understand their cause. We conducted a field study observing 21 surgeries, conducting 12 interviews and performing 3 data validation sessions with surgeons. Using Thematic Analysis, we find that physically separating surgeons from their teams makes them more autonomous, shifts their use of perceptual senses, and turns the surgeon's assistant into the robot's assistant. We open design opportunities for the HCI field by questioning the telemanipulated approach and discussing alternatives that keep surgeons on the surgical field.

A laparoscope is a key element in Minimally Invasive Surgery (MIS) as it provides visual feedback to the surgeon. To overcome the drawbacks induced by its manual operation by a human assistant, it can be fixed on the end-effector of a robotic assistant teleoperated by the surgeon: laparoscope displacements are commanded through a master input interface (e.g., joysticks, voice control, etc.) and replicated accordingly at the slave level. In this approach, precision is of high importance to ensure a good operability by the surgeon. This is why the state-of-the-art relies on rigid laparoscope holders with high-gain PID position control, ensuring high static and dynamic precision. However, in the event of undetected obstacles, such stiff systems generate high forces that may cause harm to the patient. Rather, a compliant behaviour is desirable but it leads to a lack of precision when disturbances occur, such as the unknown friction between the trocar and the laparoscope. In this paper we present a “compliant-and-precise” laparo-scope holder with 4 active Degrees of Freedom (DoFs). Its design is based on cable transmission used for haptic interfaces, thus it exhibits very high backdrivability. The paper shows how an intelligent PID position controller can be used to compensate for unknown friction at the trocar while keeping very low PID gains and a satisfactory tracking precision.

Surgeons performing laparoscopic surgery experience distortion when perceiving the stiffness of a patient's tissues. This is due to the lever effect induced by the introduction of instruments in their patient's body through a fulcrum. To address this problem, we propose to use the comanipulation paradigm. A robotic device is connected to the handle of the instrument while simultaneously being held by the surgeon. This device applies a force on the handle that reflects the force measured at the tool tip, with a gain that depends on the lever ratio. The implementation of this method is presented on an experimental setup and a preliminary assessment experiment is presented.

Accurate endoscope localization is a key element for Computer-Assisted Laparoscopic Surgery (CALS). External localizers track the endoscope pose and reconstruct the camera geometry through a calibration matrix. Perspective-n-Points (PnP) methods estimate this matrix from a set of paired point coordinates, given by the simultaneous position of a spherical marker on the image (2D coordinates) and in the external localizer frame (3D coordinates). In this paper, the PnP calibration is restated as an iterative Perspective-n-Spheres (PnS) problem: the spherical geometry of the marker is taken into account when computing the projection of its 3D center into the 2D image plane. Using calibration residuals as evaluation matrix, the proposed PnS provides better results compared to the State-of-the-Art (SoA) PnP methods. Furthermore, results show that the calibration yields different estimates due to different camera poses in the working volume. This is assumed to result from a lack of absolute precision in the marker localization across the external localizer workspace.

In this paper, a control solution featuring an energetic constraint is developed to improve the safety of a robotic manipulator sharing its workspace with humans. This general control structure, exploits a generic safe controller that ensures the respect of multiple constraints thanks to a Linear Quadratic Problem formulation. With a unified energetic formulation, the controller allows to explicitly limit both the kinetic energy when moving and the wrench applied to the environment in case of contact with an unexpected obstacle. This control approach is experimented on a redundant Kuka LWR4+ robot which end-effector shall precisely point toward a given location while following a trajectory.

International audience

Assist-as-needed control aims at maximizing stroke survivors involvement during robotic-led therapies of neurorehabilitation. Besides the specific characteristics of the designed adaptive control strategy, a fundamental property of this control architecture is the choice of the error signal which will drive the adaptation process. This driving source is a necessary control parameter to be chosen, although often sidelined in the control design, and several solutions already exist in the state-of-the-art. For this reason, we wanted to compare three different strategies to guide the adaptation, respectively based on the local joint performances, on the end-effector only behaviour, or on the performance of one specific joint in the kinematic chain of the robot. The resulting analysis evaluates the possibilities offered by simply changing from one source to another with respect to the specific stage of the motor recovery of the patients, potentially extending the capabilities of current exoskeleton controllers for neurorehabilitation.

The comanipulation paradigm, in which a user and a robot simultaneously hold a tool, allows for gesture guidance. In particular, virtual fixtures, which are geometrical constraints imposed to the tool by the robot, have received great interest in the domain of surgical applications. So far, this concept has been implemented in the context of open surgery. This paper explores the application of virtual fixtures for minimally invasive surgery, in which the tool is inserted in the patient through a fulcrum. Here, a key issue is to return to the surgeon forces that are virtually applied at the instrument distal tip, while the robot is physically attached to the instrument proximal handle. To this aim, two approaches are investigated. A first approach consists of applying a full wrench at the proximal end of the instrument that is equal to the wrench constituted by a pure force applied to the instrument's distal tip. A second approach consists of applying a pure force to the instrument proximal end, thanks to a lever model about the fulcrum. The two approaches are compared through experiments, during which naive subjects blindly perform virtual object palpation and robot-guided movements. During experiments, indicators involving motion and force analysis are computed. The user capacity to distinguish between several virtual objects is evaluated as well. Although drastically different, the two approaches provide assistance with a similar level of efficiency.

In endoscopic surgery, trocars impose kinematic constraints. Whenever a robot manipulates endoscopic instruments, it needs to know the trocar location with respect to its base frame. In the literature, this knowledge is acquired thanks to an installation / registration procedure, prior to the operation. In this paper, we are considering a comanipulation scenario: Both the robot and the surgeon hold the instrument. All along a procedure, the instrument can be inserted into or removed from different trocars by the surgeon. It is needed to detect in real time whether the instrument is inserted in a trocar and to compute the fulcrum coordinates. The proposed algorithm is described in terms of both theory and practical realization. Its effectiveness is verified experimentally.

Localizing a bone hidden behind soft tissue is crucial in biomechanics. A typical approach consists in placing markers on the skin, measuring their position/orientation, and from these measurements, estimating the position and orientation of the bone hidden behind the skin while compensating of soft tissue deformations. In this paper, we present a new method to address this problem. It requires to initially record scattered spacial transformations between the rigid body and the markers. Then, a natural neighbors interpolation algorithm, modified to apply to homogeneous transformations, is proposed. The presented method is validated on a robot manipulator on which soft tissue is placed.

This paper presents a biomechanical model for tissue deformations in the case of tangential micro-probe scanning for image acquisition. The tissue is modelled as a rigid body and its deformations - considered as elastic - as springs between this body and a fixed reference body. The contact between the probe and the tissue is then considered as a Hertzian sphere-plane contact with a Coulomb friction force. Given those hypotheses, an analytical model of the tissue deformations for 2D tangential movements along the locally planar tissue surface can be established. Similarly to the work of Erden et al. [1], the model has a unique parameter: the loading distance of the tissue. For given scan conditions, this parameter can be calibrated with a simple back-and-forth movement and image measurements. It is of particular interest in minimally invasive surgery where measurements of the friction forces or of the mechanical parameters of the tissue are complex to carry out. Simulations are in accordance with experiments and show that this model allows for accurate estimation of the probe/tissue trajectory in one dimension scans. Moreover, unlike previous studies, the model allows the estimation of the probe/tissue trajectory also for 2D scans. Both coupling behaviour and stick/slip transitions when scanning direction changes are taken into account. However experiments show that anisotropy is an important parameter when studying 2D coupling behaviour. Therefore, an extension of the model that takes anisotropic behaviour of the tissue into account is proposed. Experiments carried out on ex vivo bovine liver and chicken muscle tissues show that the probe/tissue trajectory is accurately predicted by the model. However, this increases the number of parameters to five. As a consequence, unlike in the isotropic case, the parameters can not be simply calibrated using a back-and-forth movement. Further work will be carried out towards finding an easy and effective calibration procedure that applies both to the isotropic and anisotropic cases.

This paper presents the mechanical design of a distal scanner to perform a spiral scan for mosaic-imaging with a confocal microlaparoscope. First, it is demonstrated with ex vivo experiments that a spiral scan performs better than a raster scan on soft tissue. Then a mechanical design is developed in order to perform the spiral scan. The design in this paper is based on a conic structure with a particular curved surface. The mechanism is simple to implement and to drive; therefore, it is a low-cost solution. A 5:1 scale prototype is implemented by rapid prototyping and the requirements are validated by experiments. The experiments include manual and motor drive of the system. The manual drive demonstrates the resulting spiral motion by drawing the tip trajectory with an attached pencil. The motor drive demonstrates the speed control of the system with an analysis of video thread capturing the trajectory of a laser beam emitted from the tip.

A novel robotic device, aimed at assisting a urologist in performing prostate biopsies guided by an endorectal ultrasound probe, is described. The paper describes the robot kinematics and the actuation system. The actuation system combines electromagnetic brakes, balancing springs, and electrical motors with cable transmissions. The robot supports two modes of operation: the free mode, where the entire control of the probe movements is left to the urologist, and the blocked mode, where the robot precisely maintains the probe at a given position and orientation with respect to the prostate. For the blocked mode, the set of specifications is antagonistic: firstly, a security constraint requires a low robot stiffness to allow to compliantly adapt to potential movements from the patient; secondly, a precision constraint requires a high robot stiffness in order to maintain the position and orientation of the probe in the presence of unmodeled external forces, when the robot is switched from the free mode to the blocked mode. A control strategy is developed to obtain this behavior. It combines an inner impedance controller with a relatively low stiffness and an outer intelligent position integrator that operates only during a limited period of time, when switching from the free mode to the blocked mode. Both in vitro and in cadavero experimental results show the efficiency of this approach.

Supplementary visual, audio and tactile inputs have been shown to enhance postural control. In particular the light touch on a stable surface has been proven to significantly increase postural stability. Furthermore, it has been reported that the Center of Pressure (CoP) can be sinusoidally driven thanks to somatosensory inputs. In this paper, these results are extended to improve balance control. A closed loop control of the CoP position based on somatosensory feedback is developed. This control strategy allows both setpoint tracking and path following of the CoP. The effectiveness of the proposed somatosensory feedback is assessed through experiments involving 11 naive subjects.

Current trends in robotic cardiac surgery presage for allowing physiological motion compensation in beating-heart surgery. However, interacting with fast moving soft organs by means of stiff instruments/robots is challenging. This paper concerns comanipulation with a hand-held instrument, the goal being to allow the surgeon to perform low frequency motions that correspond to the surgical task while a distal part of the instrument actively moves in synchronism with the heart motion in order to guarantee that the contact is maintained. This paper explores the difficulties of implementing low-impedance control on a novel hand-held motion compensation instrument. A force feedback control strategy is proposed and evaluated experimentally on a simulated surgical scene. Taking advantage of the sensory capacities of the prototype presented, a successful modulation of the dynamics of interaction is reached. Conclusive results on the performances of the system and possibilities of future improvements are given.

This paper presents an approach for understanding the soft tissue behavior in surface contact with a hard object scanning the tissue. The application domain is confocal microlaparoscope imaging, mostly used for imaging the outer surface of the organs in the abdominal cavity. The probe (optic-head) is swept over the tissue to collect sequential images to obtain a large field of view with mosaicing. The problem we address is that the tissue also moves with the probe due to its softness; therefore the resulting mosaic is not in the same shape and dimension as traversed by the probe. Our approach inspires from the finger slip studies and adapts the idea of load-and-slip that explains the movement of the finger when dragged on a hard surface. We propose the concept of loading-distance and perform measurements with in total 84 experiments on beef liver and chicken breast tissues. Our results indicate that the loading-distance can be measured prior to a scan and be used during the scan in order to compensate the movement of the probe. In this way we can have an image-mosaic of the tissue surface in a desired shape.

This paper deals with the problem of computing trajectories for an exoskeleton that match a motion recorded on a given subject. Literature suggests that this problem can be solved by reconstructing the subject's joint motion using one of the numerous models available, and then feeding the exoskeleton with the joint trajectories. This is founded on the assumption that the exoskeleton kinematics reproduces the human kinematics. In practice, though, mismatches are unavoidable and lead to inaccuracies. We thus developed a method that is primarily based on an appropriate mechanical design: passive mechanisms are used to connect the exoskeleton with splints wore by the subject, in such a way that, within the workspace, there always exists a posture of the exoskeleton compatible with a given position and orientation of the splints. The trajectory computing method, by itself, consists of recording the position and orientation of the splints thanks to a conventional 3D motion tracker and to exploit standard robotics tools in order to compute an exoskeleton posture compatible with the measured human posture. Conclusive experimental results involving an existing 4 DoF upper-limb exoskeleton are shown.

Probe-based confocal laser endomicroscopy is a recent tissue imaging technology that requires placing a probe in contact with the tissue to be imaged and provides real time images with a microscopic resolution. Additionally, generating adequate probe movements to sweep the tissue surface can be used to reconstruct a wide mosaic of the scanned region while increasing the resolution which is appropriate for anatomico-pathological cancer diagnosis. However, properly controlling the motion along the scanning trajectory is a major problem. Indeed, the tissue exhibits deformations under friction forces exerted by the probe leading to deformed mosaics. In this paper we propose a visual servoing approach for controlling the probe movements relative to the tissue while rejecting the tissue deformation disturbance. The probe displacement with respect to the tissue is firstly estimated using the confocal images and an image registration real-time algorithm. Secondly, from this real-time image-based position measurement, the probe motion is controlled thanks to a simple proportional-integral compensator and a feedforward term. Ex vivo experiments using a Stäubli TX40 robot and a Mauna Kea Technologies Cellvizio imaging device demonstrate the effectiveness of the approach on liver and muscle tissue.

When developing robotic exoskeletons, the design of physical connections between the device and the human limb to which it is connected is a crucial problem. Indeed, using an embedment at each connection point leads to uncontrollable forces at the interaction port, induced by hyperstaticity. In practice, these forces may be large because in general the human limb kinematics and the exoskeleton kinematics differ. To cope with hyperstaticity, the literature suggests the addition of passive mechanisms inside the mechanism loops. However, empirical solutions that are proposed so far lack proper analysis and generality. In this paper, we study the general problem of connecting two similar kinematic chains through multiple passive mechanisms. We derive a constructive method that allows the determination of all the possible distributions of freed degrees of freedom across different fixation mechanisms. It also provides formal proofs of global isostaticity. Practical usefulness is illustrated through two examples with conclusive experimental results: a preliminary study made on a manikin with an arm exoskeleton controlling the movement (passive mode) and a larger campaign on ten healthy subjects performing pointing tasks with a transparent robot (active mode).

Robotic exoskeletons can apply forces distributed on the limbs of the subject they are connected to. This offers a great potential in the field of neurorehabilitation, to address the impairment of interjoint coordination in hemiparetic stroke patients. In these patients, the normal flexible joint rotation synergies are replaced by pathological fixed patterns of rotation. In this paper, we investigate how the concept of synergy can be exploited in the control of an upper limb exoskeleton. The long term goal is to develop a device capable of changing the joint synchronization of a patient performing exercises during rehabilitation. The paper presents a controller able of generating joint viscous torques in such a way that constraints on joint velocities can be imposed to the subject without constraining the hand motion. On another hand, the same formalism is used to describe synergies observed on the arm joint motion of subjects realizing pointing tasks. This approach is experimented on a 4 Degrees Of Freedom (DoF) upper arm exoskeleton with subjects performing pointing 3-dimensional tasks. Results exhibit the basic properties of the controller and show its capacity to impose an arbitrary chosen synergy without affecting the hand motion.

The possibility to provide an adequate task assistance using underactuated robots for human-robot tool comanipulation is investigated. This novel approach does not take into account any a priori knowledge about user depending parameters however optimizes the robot-user synergy, for instance during US breast examinations. Results show that the examination time can be reduced and a tendency for increasing scanning accuracy using underactuated robots.

This paper presents a novel needle path planning method for biopsy guided by digital breast tomosynthesis (DBT) taking into account breast heterogeneity. First, a multi-resolution optimization approach, guaranteeing that a relevant path is computed, is proposed. Moreover, local breast mechanical parameters required for a heterogeneous finite element simulation, are extracted from the DBT data. The proposed approach computes a 3D local breast glandularity estimation used for Young's modulus determination. This planning method, using a heterogeneous model, reduces the tool positioning error meanly by 75%. In addition, the results show that a breast heterogeneous model has the potential to improve planning accuracy.

Shape and mechanical structure of instruments play a large part in the lack of ergonomics during laparoscopic surgery. Providing intra-abdominal mobility and rethinking handles design are two solutions to increase comfort and precision of gestures. Based on previous work that determined the optimal intra-abdominal kinematics, this study analyses the influence of handle design on both gesture and ergonomic performance. A virtual reality laparoscopic simulator was developed to perform an experimental comparison between two novel robotized instruments and standard ones. A group of 10 surgeons and 6 researchers in robotics carried out two representative surgical tasks with each instrument. Based on instrument and arm segments tracking, a gesture performance index and an ergonomic performance index were computed. The study demonstrates that distal mobilities combined with improved handle design and integration increase ergonomic level during laparoscopy and facilitate complex gestures.

Probe-based confocal laser endomicroscopy is a promising technology for performing minimally-invasive optical biopsies. With the help of mosaicing algorithms, several studies reported successful results in endoluminal surgery. In this paper, we present a prototype for making robotized optical biopsies on a variety of organs inside the abdominal cavity. We chose a macro-micro association, with a macropositioner, a micropositioner and a passive mechanical compensation of physiological motion. The probe is actuated by three hydraulic micro-balloons and can be moved on the surface of an organ to generate a mosaic. This paper presents the design and experimental results of a first in vivo trial on a porcine model.

This article proposes a control scheme for robot assisted laser osteotomy. Laser osteotomy consists in cutting a bone precisely with a laser. To achieve accurate cuts the laser has to be precisely sent to a desired pose with respect to the bone. In the proposed approach, a robot is used to position an end-effector with a scanhead, which deflects the cutting laser. The poses of the laser and of the bone are measured thanks to an optical tacking system which tracks the positions of optical markers placed on the bone and on the scanhead. The control of the robot is then performed thanks to a position-based visual servoing control scheme. In the case of bones affected by breathing motions, for instance the thorax bones, this control scheme is enhanced with a learning algorithm in order to compensate breathing motions. The main contribution of this paper is this control algorithm for motions compensation.

The design of a robotic exoskeleton often focuses on replicating the kinematics of the human limb that it is connected to. However, human joint kinematics is so complex that in practice, the kinematics of artificial exoskeletons fails to reproduce it exactly. This discrepancy results in hyperstaticity. Namely, uncontrolled interaction forces appear. In this paper, we investigate the problem of connecting an exoskeleton to a human member while avoiding hyperstaticity; to do so, we propose to add passive mechanisms at each connection point. We thus introduce a formal methodology for avoiding hyperstaticity when connecting wearable robotic structures to the human body. First, analyzing the twist spaces generated by these fixation passive mechanisms, we provide necessary and sufficient conditions for a given global isostaticity condition to be respected. Then, we derive conditions on the number of Degrees of Freedom (DoFs) to be freed at the different fixations, under full kinematic rank assumption. We finally apply the general methodology to the particular case of a 4 DoF shoulder-elbow exoskeleton. Experimental results allow to show an improvement in transparency brought by the passive mechanism fixations.

This paper presents a new needle path planning method for digital breast tomosynthesis biopsy. Needle insertion planning into deformable tissue for breast biopsy procedure is a challenging task because of the infinite possibilities of insertion points. In addition, the lesion moves from its original position when the radiologist introduces the biopsy needle. The proposed approach couples Rapidly-exploring Random Trees with Finite Element Simulation in order to find an optimal path taking breast deformations into account. Simulation results show that this method reduces the error (i.e. the distance between the needle tip and the lesion) by 80%.

One of the key features of upper limb exoskeletons is their ability to take advantage of the human arm kinematic redundancy in order to modify the subject's joint dynamics without affecting his/her hand motion. This is of particular interest in the field of neurorehabilitation, when an exoskeleton is used to interact with a patient who suffers from joint motions desynchronization, resulting e.g. from brain damage following a stroke. In this paper, we investigate this problem from the robot control point of view. A first general controller is derived which uses viscous force fields in order to generate joint torques counteracting any velocities that are perpendicular to a given set of constraints. In order to minimize energy dissipation, a second controller is proposed that still uses viscous force fields, but in a way that the mechanical power dissipated by the viscous control is null at any time. This controller does not impose any trajectory to the hand and the robot only moves in response to the forces generated by the patient. This approach is experimented on a 4-DOF exoskeleton with a healthy subject. Results exhibit the basic properties of the controller and show its capacity to impose an arbitrary chosen joint constrain for 3-DOF pointing tasks without constraining the hand motion.

In the field of comanipulation (i.e. a man and a robot sharing the same task), force amplification is an interesting function that can be achieved by using two force sensors. This technique is known in the literature but little attention has been paid so far to stability/passivity properties. We will explain how to deal with passivity based stability criteria, and point out performance limitations of such a control in case of noncollocated and bandwidth limited force sensors. Theoretical, as well as experimental results will be presented.

We focus on comanipulation, i.e. manipulation of an object simultaneously held by a robot and a human operator. In this domain, a major difficulty is raised by significant variations of human dynamics, which depend not only on the arm posture, but also on the muscular activity (muscular co-contraction) and more generally on the type of task being performed: fine positioning, gross and rapid movements, repeated movements, etc. An ideal comanipulation system should be able of adapting its behavior to the operator's functional intention, resulting in an intuitive assisting device. Toward this goal, we present in this paper first results of our research aimed at developing an instrumented handle mounted on a robot end-effector and held by an operator, that can be used for estimating the grasping force and for adapting the robot controller accordingly. We show first experimental evidences that changes in the grasping force drastically affect the robot controller performances. We thus propose a handle design and a gain scheduling strategy that result in a robot behavior adequate for any kind of grasps. This solution is successfully experimented with a 1 degree of freedom robot under largely variable comanipulation conditions, exhibiting a stable and efficiently adaptive behavior.

The proposed robotic system provides the surgeon with an augmented sensation of the interaction forces between the instrument and the organ. Such a system aims at increasing the surgeon's dexterity for tasks requiring that only small forces be applied on the organ (eg. for micro-surgery). In the proposed setup, the surgeon manipulates a handle mounted on the instrument. This is a comanipulation system because the surgeon and the robot simultaneously manipulate the instrument. The proposed control scheme allows an augmented force control: the control law ensures that the instrument applies on the organ the same forces that the surgeon applies on the handle but decreased by a scale factor. As a consequence, the forces sensed by the surgeon are the forces between the instrument and the organ amplified by a scale factor. This control scheme is proved stable thanks to a passivity study. Indeed, passivity analysis is a useful tool for the stability analysis of a robot interacting with the environment. Experimental results are presented on a robot dedicated to minimally invasive surgery.

A major issue in the field of human-robot interaction for assistance to manipulation is transparency. This basic feature qualifies the capacity for a robot to follow human movements without any human-perceptible resistive forces. In this paper we address the issue of human motion prediction in order to increase the transparency of a robotic manipulator. Our aim is not to predict the motion itself, but to study how this prediction can be used to improve the robot transparency. For this purpose, we have designed a setup for performing basic planar manipulation tasks involving movements that are demanded to the subject and thus easily predictable. Moreover, we have developed a general controller which takes a predicted trajectory (recorded from offline free motion experiments) as an input and feeds the robot motors with a weighted sum of three controllers: torque feedforward, variable stiffness control and force feedback control. Subjects were then asked to perform the same task but with or without the robot assistance (which was not visible to the subject), and with several sets of gains for the controller tuning. First results seems to indicate that when a predictive controller with open loop torque feedforward is used, in conjunction with force- feedback control, the interaction forces are minimized. Therefore, the transparency is increased.

We present a new device aimed at being used for upper limb rehabilitation. Our main focus was to design a robot capable of working in both the passive mode (i.e. the robot shall be strong enough to generate human-like movements while guiding the weak arm of a patient) and the active mode (i.e. the robot shall be able of following the arm without disturbing human natural motion). This greatly challenges the design, since the system shall be reversible and lightweight while providing human compatible strength, workspace and speed. The solution takes the form of an orthotic structure, which allows control of human arm redundancy contrarily to clinically available upper limb rehabilitation robots. It is equipped with an innovative transmission technology, which provides both high gear ratio and fine reversibility. In order to evaluate the device and its therapeutic efficacy, we compared several series of pointing movements in healthy subjects wearing and not wearing the orthotic device. In this way, we could assess any disturbing effect on normal movements. Results show that the main movement characteristics (direction, duration, bell shape profile) are preserved.

In recent years, there has been an increasing interest in developing systems that couple a robotic device with an ultrasound imager. Applications range from automatic probe positioning to ultrasound image-based guidance of instruments. One issue in these systems is to determine, prior to the intervention, the localization of the probe with respect to the robot. Literature suggests using external localizers, but they add to the complexity of the system, and the resulting precision is usually not good due to the addition of errors in the kinematic chain. In this paper, we study the hand-eye calibration problem without using any additional localizers. A generic system consisting of a fixed probe observing an instrument manipulated by a robot is used. We first derive a simplified model for mapping the image of the instrument with its 3D location w.r.t. the probe and then propose a calibration procedure based on a minimization algorithm. Results show that although very simple models were used for the imaging device, the localization is quite precise, as it results in errors of less than 2 mm, which is enough of a number of ultrasound guided interventions.

This paper presents a force feedback control scheme for the compensation of periodic motions of organs induced by respiration or heartbeat in minimally invasive robotized surgery. It applies surgical tasks involving a contact between an instrument and a moving organ. It is well known that conventional force control allows for compensating the motion of the environment thanks to its natural disturbance rejection capabilities. However, as experimentally evidenced in the first part of this paper, bandwidth limitations do not allow for exact disturbance rejection. Therefore, in addition to a conventional inner force feedback control loop, an outer control loop based on iterative learning control (ILC) is implemented. It is aimed at compensating the physiological motions, based on the hypothesis that the disturbance is periodic. The transient performances of this ILC controller are improved thanks to a wavelet transform-based approach and conclusive experiments are finally presented, evidencing that the tracking performance under cyclic disturbances is significantly improved.

This paper proposes a novel planning algorithm for image based visual servoing (IBVS). IBVS is conceptually simple but prone to fail in case of large displacements. Hence, the objective is to provide paths for reference points in the image plane, such that the camera is steered from initial position to desired position. The novel scheme guarantees that the camera is always oriented such that the object of interest is in the field of view and that any reference point set corresponds indeed to a feasible camera pose. No camera calibration is necessary. As a novelty, this work is planning a camera motion, hence yielding compact paths in robot work space. The proposed planner is compared to others by experiments.

This paper presents a robust visual servoing approach for automatic guidance of an instrument. The visual sensor is an ultrasound probe that observes an instrument which is inserted into the beating heart of a patient and manipulated by a robot. The present paper provides stability analysis, robustification of the control law and an in vivo experiment.

In this paper, we present an iterative method for positioning a patient in protontherapy. The main difficulty in this kind of treatment is the unknown position of the treated volume during the set up of the patient. The positioning process is realized by a 6 degrees of freedom (DOF) industrial robot. This article explains how the positioning error of the treated volume can e minimized thanks to an external tracking system.

Measuring human movement in real time is of primary importance in a number of new applications of interactive systems and human centered robotics. A major difficulty in this field arises from the high joint redundancy of the human kinematics. Conventional approaches address this problem by installing a rather large number of sensors or markers on the subject. On the other hand, well admitted theories in neurosciences claim that joint synchronization in human movements is governed by so-called synergies, that can be viewed as joint patterns corresponding to a given gesture of a given individual. In this paper, we intend to exploit this property in order to reduce the number of sensors to be installed on a human subject when tracking his/her motion. Namely, our suggested method comprizes two phases. In a learning stage, the subject is asked to complete a given gesture a few times, while he/she is equipped with sensors able to measure his/her full posture. An algorithm is thus used in a second phase to reduce the required number of sensors while reconstructing the whole posture of the subject. Experimental evidence is provided for the particular motion of sit-to-stand transfer, in a study that involves healthy subjects.

In this article, the problem of force feedback control of kinematically constrained manipulators (KCMs) is considered. For these robots, we show that the force component selection approach is not appropriate in general to solve the force control problem. Moreover, by formulating the problem in the joint space, we show how to properly design a stable force controller for KCMs subject to arbitrary external forces applied to their end-effector. Experimental results with a kinematically constrained laparoscopic comanipulator illustrate these propositions

We consider the problem of planning a path for image-based eye-in-hand visual servoing applications, when using an uncalibrated camera. Recent developments in this field lead to analytical interpolation between two views of an unknown object, in the projective space. Literature also provides extensions of these approaches that account for the target visibility constraint. Unfortunately, these extensions require an (even weakly) calibrated camera, and involve iterative algorithms that are not proven to converge. In this paper, we propose a modification of an existing projective interpolation algorithm that guarantees the visibility of the observed target, while avoiding the use of any knowledge on the camera calibration parameters, nor on the observed object

Minimally invasive surgery in combination with ultrasound (US) imaging imposes high demands on the sur geon’s hand-eye-coordination capabilities. A possible solution to reduce these requirements is minimally invasive robotic surgery in which the instrument is guided by visual servoing towards the goal defined by the surgeon in the US image. This approach requires robust tracking of the instrument in the US image sequences which is known to be difficult due to poor image quality. This paper presents computer vision algorithms and results of visual servoing experiments. Adaptive thresholding according to Otsu’s method allows to cope with large intensity variations of the instrument echo. Subsequently applied morphological operations suppress noise and echo artefacts. A fast labelling algorithm based on run length coding allows for realtime labelling of the regions. A heuristic exploiting region size and region velocity helps to overcome ambiguities. The overall computation time is less than 10 ms per frame on a standard PC. The tracking algorithm requires no information about texture and shape which are known to be very unreliable in US image sequences. Experimental results for different instrument materials (polyvinyl chloride, polyurethane, nylon, and plexiglas) are given, illustrating the performance of the proposed approach: when chosing the appropriate material the reconstructed trajectories are smooth and only few outliers occur. As a consequence, the visual servoing loop showed to be robust and stable.

Visual servoing is a possible solution to assist the surgeon in performing tasks under ultrasound (US) imaging. To this aim, a system was developed that allows the surgeon to select a desired instrument location on a US image. Then a robot is programmed to automatically move the instrument towards the selected location. This approach requires robust tracking of the instrument in the US image, together with modeling of the overall system and implementation of a visual servoing loop. This paper presents geometrical and kinematic models of the system, as well as the control loop design, which is validated through both numerical simulations, and results of in vitro experiments.

Trajectory planning for eye-in-hand visual servoing is usually performed in the Euclidean work space of the robot or in a two dimensional image space. However, planning in Euclidean space may lead to very inappropriate trajectories in image space and vice versa. These difficulties are due to the perspective transformation of the camera, loss of one dimension due to projection onto the image plane and the fact that only a rough approximation of camera parameters is practically available. Hence, this paper proposes a planning scheme for image trajectories such that straight line behaviour is ensured both in image space and world space, ie. a single but arbitrarily chosen point in the image plane performs straight line behaviour as well as the camera optical center in work space. This way, trajectories become very compact and most of the above mentioned problems are avoided in a natural way. The algorithm requires as a priori information nothing more than matched image points (in pixels) from a current and desired image and a depth set for at least one position.

This paper introduces an original, dextrous, active and modular minimally invasive instrument dedicated to coronary artery bypass grafting surgery. Its design is obtained by a generic evolutionary optimization process using Pareto-based multi objective genetic algorithms and including highly realist simulations and experimental models of the surgical gesture. The optimal instrument has 5 intra-body DOFs, is actuated by brush-less micro motors and is position controlled. Its optimization, mechanical design and performances are discussed.

This work deals with trajectory planning for image based eye-in-hand visual servoing applications. Trajectories for extracted feature points of a target object are computed directly in the projective image space such that they are compatible with rigid body displacements. To this end, one separately parameterizes for: (a) the collineation with respect to the plane at infinity (which can be viewed as a projective representation of the rotation); and (b) the projective representation of the translation. Parameterizing the collineation by the use of decomposition into its canonical form provides an easy way to plan for a geodesic displacement. Furthermore, different strategies are proposed to interpolate for the translation path. As a result, the most advanced strategy guarantees, by the use of a simple analytic criterion, that the points remain visible during the whole path. The method requires in general nothing more than the initial and final images and does not depend on intrinsic camera parameters.

This work presents a novel visual servoing approach, aimed at controlling the so-called extended-2D (E2D) coordinates of the points constituting a tracked target. This approach does not require any pose reconstruction. Rather, the only information required to build the E2D coordinates are the estimated depth distribution of the target points, and the estimated camera model. Several implementations of the controller are considered, which are inspired from conventional image based visual servoing from points. In spite of their simplicity, the proposed control laws exhibit remarkable stability robustness properties. A key issue is that only three configurations of undesired equilibrium exist, and they are all proven to be unstable even in the uncalibrated case. In other words, contrarily to existing 2D methods, there are no local minima. The paper details the control design and analysis and provides simulation results, emphasizing the remarkable robustness with respect to camera calibration errors.

Force-feedback mechanisms have been designed to simplify and enhance the human-vehicle interface. The increase in secondary controls within vehicle cockpits has created a desire for a simpler, more efficient human-vehicle interface. By consolidating various controls into a single, haptic feedback control device, information can be transmitted to the operator, without requiring the driver's visual attention. In this work, the experimental closed loop torque control of electro-rheological fluids (ERF) based actuators for haptic application is performed. ERFs are liquids that respond mechanically to electric fields by changing their properties, such as viscosity and shear stress, electroactively. Using the electrically controlled rheological properties of ERFs, we developed actuators for haptic devices that can resist human operator forces in a controlled and tunable fashion. In this study, the ERF actuator analytical model is derived and experimentally verified and accurate closed loop torque control is experimentally achieved using a non-linear proportional integral controller with a feed-forward loop.

In this paper, we present a method to plan and control the 6 DOF displacements of a manipulator from an eye-in-hand camera image. With this method, even in the presence of camera calibration errors, we can formally guarantee that the system is stable and that the entire target remains visible during any visually servoed motion.

Minimally invasive surgery (MIS) challenges the surgeon's skills due to his separation from the operation area, which can be reached with long instruments only. Therefore, the surgeon loses access to the manipulation forces inside the patient. This reduces his dexterity when performing the operation. A new compact and lightweight robot for MIS is presented which allows for the measurement of manipulation forces. The main advantage of this concept is that no miniaturized force sensor has to be integrated into surgical instruments and inserted into the patient. Rather, outside the patient a standard sensor is attached to a modified trocar, which allows for the undisturbed measurement of manipulation forces. This approach reduces costs and sterilizability demands. Results of first force control experiments are presented to show the feasibility of the concepts.

This paper presents a robotic vision system that automatically retrieves and positions surgical instruments during robotized laparoscopic surgical operations. The instrument is mounted on the end-effector of a surgical robot which is controlled by visual servoing. The goal of the automated task is to safely bring the instrument at a desired three-dimensional location from an unknown or hidden position. Light-emitting diodes are attached on the tip of the instrument, and a specific instrument holder fitted with optical fibers is used to project laser dots on the surface of the organs. These optical markers are detected in the endoscopic image and allow localizing the instrument with respect to the scene. The instrument is recovered and centered in the image plane by means of a visual servoing algorithm using feature errors in the image. With this system, the surgeon can specify a desired relative position between the instrument and the pointed organ. The relationship between the velocity screw of the surgical instrument and the velocity of the markers in the image is estimated online and, for safety reasons, a multistages servoing scheme is proposed. Our approach has been successfully validated in a real surgical environment by performing experiments on living tissues in the surgical training room of the Institut de Recherche sur les Cancers de l'Appareil Digestif (IRCAD), Strasbourg, France.

This paper presents a robotic vision system that automatically retrieves and positions surgical instruments in robotized laparoscopic surgery. The surgical instrument is mounted on the end-effector of a surgical robot which can be controlled by automatic visual feedback. The goal of the automated task is to bring the instrument at a desired location from an unknown or hidden position. To achieve this task, a special instrument-holder is designed with optical fibers and collimators. This instrument-holder projects laser dot patterns onto the organ surface which are seen in the endoscopic images. Then, the instrument is retrieved and centered in the image plane using a visual servoing algorithm. With this system, the surgeon can also specify a desired position for the instrument in the image. Our approach is successfully validated in a real surgical environment by performing experiments on living animals in the surgical training room of IRCAD.

In this paper, we present a new solution to laparoscopic manipulation based on force feedback control. This method allows to both explicitly control the forces applied to the patient through the trocar, and to precisely control the position of the surgical instrument. It does not require any geometrical model of the operative environment, nor any fine robot base placement prior to the instrument insertion. Different control strategies, involving different kinds of sensory equipments are proposed. They are experimentally validated on a laboratory apparatus.

This paper focuses on the design of robust motion rate sensor based control of robots. Considering the widely used task function approach of this problem, we first derive a general condition on the control gains with respect to the uncertainties, so as to guarantee bounded tracking errors. This general result is applied to an example case, consisting of a 2-DOF vision based controller. Experimental results of comparing different control strategies are presented.

Using an industrial manipulator as a slave arm in a force-feedback teleoperation system requires to us deal with its poor backdrivability. Improving transparency of such a system, using a wrist force/torque sensor, is known as an effective and robust method. Another solution could be to use a base force/torque sensor. The paper focuses on the feasibility of such an approach in a force-feedback teleoperation context. It is then compared to a wrist force/torque sensor approach.

We use sliding mode control theory to design a 3D vision based controller that is robust to bounded parametric estimation errors. First, a model of an eye-in-hand robotic system is derived and sources of uncertainties are listed. Additionally, bounds on the different uncertainties are discussed and their influence on the overall gain of the system is derived. Due to an appropriate selection of the sliding surface, based on the quaternion representation for rotations, a switching controller is proposed. Six degrees of freedom vision based tracking experiments under weak calibration conditions emphasize the practical efficiency of the algorithm.

A practical method is proposed for estimating the inertial parameters of robot manipulators with substantial unmodeled joint friction and actuator dynamics. The manipulator is mounted on a six-axis force/torque sensor. Sensor measurements and joint velocities recorded during manipulator motion are used to identify the inertial parameters. The unmodeled joint friction and actuator dynamics do not degrade the estimation results, as in conventional methods. The estimation algorithm does not require difficult-to-measure acceleration measurements. Experimental results presented show that an accurate estimation of inertia parameters is attainable. Since the sensor is external to the manipulator, the same sensor can be used for parameter estimation for a number of different systems.

We propose a simple and efficient control algorithm that combines visual servo control and force feedback within the impedance control approach. The control scheme involves, at the low level, a position based impedance controller with an external force sensor feedback loop. The reference trajectory fed to this impedance controller is generated online by a vision based control loop. In spite of its simplicity, this approach provides satisfactory experimental behavior. Peg in hole insertion experiments involving large initial errors, are performed using a 7 axis robot manipulator without any computation of the peg trajectory.

This paper proposes the distributed impedance approach as a new formulation of multiple robot systems control. In this approach, each cooperating manipulator is provided with its own independent impedance controller. In addition, along selected degrees of freedom, force control is achieved through an external loop, in order to improve control of the object's internal loading. Extensive stability analysis is performed based on a realistic model that includes robots impedance and object dynamics. Experiments are performed using two cooperating industrial robots holding an object through point contacts. Force and position control actions are suitably dispatched to achieve both internal loading control and object position control. The performance of the system is demonstrated for transporting tasks.

This paper presents a shape memory alloy (SMA) actuator aimed to be integrated in the phalanx of a dexterous micro-gripper. Its original design mechanically decouples motion transmission from force transmission. After a brief discussion on the operating principles of the actuator, the kinematics of the mechanism and its general features are specified. A thermo-mechanical model of the SMA fibers dynamics is then derived from an experimental analysis. Based on this model, a rational design methodology is proposed for the actuator. The last part of the paper shows experimental results. A prototype has been developed using the proposed design methodology. The paper shows the open loop results of this device. Additionally, a position switching mode controller is designed to improve precision and robustness.

Conventional force control of manipulators is drastically degraded in the presence of external dynamic disturbances. Such difficulties may occur during unexpected environment motions or sudden changes in the environment dynamics. The solution the authors have developed provides robustness with respect to these disturbances. It consists of encapsulating a dynamic impedance controller with a reactive external force loop. This paper focuses on the external loop, which takes into account both interaction forces and environment displacements to modify the reference trajectory of the inner impedance controller. It is also capable of rapid self tuning when the environment dynamics are changed. The reactive external loop is implemented using fuzzy logic techniques. Observation of the real behavior of the experimental system is used to design some simple fuzzy rules. Experimental results illustrate the efficiency and the robustness of this control method on dynamically complex tasks involving interactions between two industrial manipulators.

Joint friction is a major problem in accurately controlling robot position during manipulator tasks involving small and slow motions. Previous research in this field suggests the use of either complex modeling and identification techniques, or expensive and delicate torque sensors that must be integrated into the manipulator. This paper proposes a simple, cost-effective method for compensating the effect of joint friction, which utilizes a six-axis force/torque sensor mounted on the base of the manipulator. From the base wrench measurements, the joint torques are estimated and fed back through a torque controller, that virtually eliminates friction and gravity effects. With such high-quality torque control, a simple PD position controller is sufficient to provide high precision motion control even at very low speed and small motions. Theoretical and practical aspects of the torque estimation are first discussed. Next, the control design and tuning is shown. Experimental results for an industrial Puma manipulator, with high Coulomb friction in its gear trains, show the effectiveness of the method. The achieved precision is substantially greater than for conventional methods and approaches the resolution of the Puma's encoders.