Expert-in-the-Loop Multilateral Telerobotics for Haptics-Enabled Motor Function and Skills Development

Among medical robotics applications are Robotics-Assisted Mirror Rehabilitation Therapy (RAMRT) and Minimally-Invasive Surgical Training (RAMIST) that extensively rely on motor function development. Haptics-enabled expert-in-the-loop motor function development for such applications is made possible through multilateral telerobotic frameworks. While several studies have validated the benefits of haptic interaction with an expert in motor learning, contradictory results have also been reported. This emphasizes the need for further in-depth studies on the nature of human motor learning through haptic guidance and interaction. The objective of this study was to design and evaluate expert-in-the-loop multilateral telerobotic frameworks with stable and human-safe control loops that enable adaptive “hand-over-hand” haptic guidance for RAMRT and RAMIST. The first prerequisite for such frameworks is active involvement of the patient or trainee, which requires the closed-loop system to remain stable in the presence of an adaptable time-varying dominance factor. To this end, a wave-variable controller is proposed in this study for conventional trilateral teleoperation systems such that system stability is guaranteed in the presence of a time-varying dominance factor and communication delay. Similar to other wave-variable approaches, the controller is initially developed for the Velocity-force Domain (VD) based on the well-known passivity assumption on the human arm in VD. The controller can be applied straightforwardly to the Position-force Domain (PD), eliminating position-error accumulation and position drift, provided that passivity of the human arm in PD is addressed. However, the latter has been ignored in the literature. Therefore, in this study, passivity of the human arm in PD is investigated using mathematical analysis, experimentation as well as user studies involving 12 participants and 48 trials. The results, in conjunction with the proposed wave-variables, can be used to guarantee closed-loop PD stability of the supervised trilateral teleoperation system in its classical format. The classic dual-user teleoperation architecture does not, however, fully satisfy the requirements for properly imparting motor function (skills) in RAMRT (RAMIST). Consequently, the next part of this study focuses on designing novel supervised trilateral frameworks for providing motor learning in RAMRT and RAMIST, each customized according to the requirements of the application. The framework proposed for RAMRT includes the following features: a) therapist-in-the-loop mirror therapy; b) haptic feedback to the therapist from the patient side; c) assist-as-needed therapy realized through an adaptive Guidance Virtual Fixture (GVF); and d) real-time task-independent and patient-specific motor-function assessment. Closed-loop stability of the proposed framework is investigated using a combination of the Circle Criterion and the Small-Gain Theorem. The stability analysis addresses the instabilities caused by: a) communication delays between the therapist and the patient, facilitating haptics-enabled tele- or in-home rehabilitation; and b) the integration of the time-varying nonlinear GVF element into the delayed system. The platform is experimentally evaluated on a trilateral rehabilitation setup consisting of two Quanser rehabilitation robots and one Quanser HD2 robot. The framework proposed for RAMIST includes the following features: a) haptics-enabled expert-in-the-loop surgical training; b) adaptive expertise-oriented training, realized through a Fuzzy Interface System, which actively engages the trainees while providing them with appropriate skills-oriented levels of training; and c) task-independent skills assessment. Closed-loop stability of the architecture is analyzed using the Circle Criterion in the presence and absence of haptic feedback of tool-tissue interactions. In addition to the time-varying elements of the system, the stability analysis approach also addresses communication delays, facilitating tele-surgical training. The platform is implemented on a dual-console surgical setup consisting of the classic da Vinci surgical system (Intuitive Surgical, Inc., Sunnyvale, CA), integrated with the da Vinci Research Kit (dVRK) motor controllers, and the dV-Trainer master console (Mimic Technology Inc., Seattle, WA). In order to save on the expert\u27s (therapist\u27s) time, dual-console architectures can also be expanded to accommodate simultaneous training (rehabilitation) for multiple trainees (patients). As the first step in doing this, the last part of this thesis focuses on the development of a multi-master/single-slave telerobotic framework, along with controller design and closed-loop stability analysis in the presence of communication delays. Various parts of this study are supported with a number of experimental implementations and evaluations. The outcomes of this research include multilateral telerobotic testbeds for further studies on the nature of human motor learning and retention through haptic guidance and interaction. They also enable investigation of the impact of communication time delays on supervised haptics-enabled motor function improvement through tele-rehabilitation and mentoring

A Wave Variable Approach with Multiple Channel Architecture for Teleoperated System

© 2013 IEEE. Performance of teleoperation can be greatly influenced by time delay in the process of tele-manipulation with respect to accuracy and transparency. Wave variable is an effective algorithm to achieve a good stable capability. However, some traditional wave variable methods may decrease the performance of transparency and suffer the impacts of wave reflection. To deal with the problem of stability and transparency in teleoperation, in this paper, a novel wave variable method with four channel is presented to achieve stable tracking in position and force. In addition, the proposed method can achieve the distortion compensation and reduce the impacts of wave reflection. The simulation experimental results verified the tracking performance of the proposed method

An Energy-Based Approach for n-dof Passive Dual-user Haptic Training Systems

International audienceThis paper introduces a dual-user training system whose design is based on an energetic approach. This kind of system is useful for supervised hands-on training where a trainer interacts with a trainee through two haptic devices, in order to practice on a manual task performed on a virtual or teleoperated robot (for example for an MIS task in a surgical context). This paper details the proof of stability of an Energy Shared Control (ESC) architecture we previously introduced for one degree of freedom (d.o.f.) devices. An extension to multiple degrees of freedom is proposed, along with an enhanced version of the Adaptive Authority Adjustment (AAA) function. Experiments are carried out with 3 d.o.f. haptic devices in free motion as well as in contact contexts in order to show the relevance of this architecture

Sensors Allocation and Observer Design for Discrete Bilateral Teleoperation Systems with Multi-Rate Sampling

This study addresses sensor allocation by analyzing exponential stability for discrete-time teleoperation systems. Previous studies mostly concentrate on the continuous-time teleoperation systems and neglect the management of significant practical phenomena, such as data-swap, the effect of sampling rates of samplers, and refresh rates of actuators on the system’s stability. A multi-rate sampling approach is proposed in this study, given the isolation of the master and slave robots in teleoperation systems which may have different hardware restrictions. This architecture collects data through numerous sensors with various sampling rates, assuming that a continuous-time controller stabilizes a linear teleoperation system. The aim is to assign each position and velocity signals to sensors with different sampling rates and divide the state vector between sensors to guarantee the stability of the resulting multi-rate sampled-data teleoperation system. Sufficient Krasovskii-based conditions will be provided to preserve the exponential stability of the system. This problem will be transformed into a mixed-integer program with LMIs (linear matrix inequalities). These conditions are also used to design the observers for the multi-rate teleoperation systems whose estimation errors converge exponentially to the origin. The results are validated by numerical simulations which are useful in designing sensor networks for teleoperation systems

A Stable and Transparent Framework for Adaptive Shared Control of Robots

In mixed-initiative haptic shared control of robots, humans and automatic control system work in parallel. The commands to the robot are a weighted sum of forces from these two agents. This thesis develops control methods to improve the force feedback performance for mixed-initiative shared teleoperation and to adapt the control authority between human and automatic control system in a stable manner even in the presence of communication delays. All methods are validated on real robotic hardware

Model-Augmented Haptic Telemanipulation: Concept, Retrospective Overview, and Current Use Cases

Certain telerobotic applications, including telerobotics in space, pose particularly demanding challenges to both technology and humans. Traditional bilateral telemanipulation approaches often cannot be used in such applications due to technical and physical limitations such as long and varying delays, packet loss, and limited bandwidth, as well as high reliability, precision, and task duration requirements. In order to close this gap, we research model-augmented haptic telemanipulation (MATM) that uses two kinds of models: a remote model that enables shared autonomous functionality of the teleoperated robot, and a local model that aims to generate assistive augmented haptic feedback for the human operator. Several technological methods that form the backbone of the MATM approach have already been successfully demonstrated in accomplished telerobotic space missions. On this basis, we have applied our approach in more recent research to applications in the fields of orbital robotics, telesurgery, caregiving, and telenavigation. In the course of this work, we have advanced specific aspects of the approach that were of particular importance for each respective application, especially shared autonomy, and haptic augmentation. This overview paper discusses the MATM approach in detail, presents the latest research results of the various technologies encompassed within this approach, provides a retrospective of DLR's telerobotic space missions, demonstrates the broad application potential of MATM based on the aforementioned use cases, and outlines lessons learned and open challenges

Modeling of Force and Motion Transmission in Tendon-Driven Surgical Robots

Tendon-based transmission is a common approach for transferring motion and forces in surgical robots. In spite of design simplicity and compactness that comes with the tendon drives, there exists a number of issues associated with the tendon-based transmission. In particular, the elasticity of the tendons and the frictional interaction between the tendon and the routing result in substantially nonlinear behavior. Also, in surgical applications, the distal joints of the robot and instruments cannot be sensorized in most cases due to technical limitations. Therefore, direct measurement of forces and use of feedback motion/force control for compensation of uncertainties in tendon-based motion and force transmission are not possible. However, force/motion estimation and control in tendon-based robots are important in view of the need for haptic feedback in robotic surgery and growing interest in automatizing common surgical tasks. One possible solution to the above-described problem is the development of mathematical models for tendon-based force and motion transmission that can be used for estimation and control purposes. This thesis provides analysis of force and motion transmission in tendon-pulley based surgical robots and addresses various aspects of the transmission modeling problem. Due to similarities between the quasi-static hysteretic behavior of a tendon-pulley based da Vinci® instrument and that of a typical tendon-sheath mechanism, a distributed friction approach for modeling the force transmission in the instrument is developed. The approach is extended to derive a formula for the apparent stiffness of the instrument. Consequently, a method is developed that uses the formula for apparent stiffness of the instrument to determine the stiffness distribution of the tissue palpated. The force transmission hysteresis is further investigated from a phenomenological point of view. It is shown that a classic Preisach hysteresis model can accurately describe the quasi-static input-output force transmission behavior of the da Vinci® instrument. Also, in order to describe the distributed friction effect in tendon-pulley mechanisms, the creep theory from belt mechanics is adopted for the robotic applications. As a result, a novel motion transmission model is suggested for tendon-pulley mechanisms. The developed model is of pseudo-kinematic type as it relates the output displacement to both the input displacement and the input force. The model is subsequently used for position control of the tip of the instrument. Furthermore, the proposed pseudo-kinematic model is extended to compensate for the coupled-hysteresis effect in a multi-DOF motion. A dynamic transmission model is also suggested that describes system’s response to high frequency inputs. Finally, the proposed motion transmission model was used for modeling of the backlash-like hysteresis in RAVEN II surgical robot

Cooperative Object Manipulation with Force Tracking on the da Vinci Research Kit

The da Vinci Surgical System is one of the most established robot-assisted surgery device commended for its dexterity and ergonomics in minimally invasive surgery. Conversely, it inherits disadvantages which are lack of autonomy and haptic feedback. In order to address these issues, this work proposes an industry-inspired solution to the field of force control in medical robotics. This approach contributes to shared autonomy by developing a controller for cooperative object manipulation with force tracking utilizing available manipulators and force feedback. To achieve simultaneous position and force tracking of the object, master and slave manipulators were assigned then controlled with Cartesian position control and impedance control respectively. Because impedance control requires a model-based feedforward compensation, we identified the lumped base parameters of mass, inertias, and frictions of a three degree-of-freedom double four-bar linkage mechanism with least squares and weighted least squares regression methods. Additionally, semidefinite programming was used to constrain the parameters to a feasible physical solution in standard parameter space. Robust stick-slip static friction compensation was applied where linear Viscous and Coulomb friction was inadequate in modeling the prismatic third joint. The Robot Operating System based controller was tested in RViz to check the cooperative kinematics of up to three manipulators. Additionally, simulation with the dynamic engine Gazebo verified the cooperative controller applying a constant tension force on a massless spring-damper virtual object. With adequate model feedback linearization, the cooperative impedance controller tested on the da Vinci Research Kit yielded stable tension force tracking while simultaneously moving in Cartesian space. The maximum force tracking error was +/- 0.5 N for both a compliant and stiff manipulated object

Haptics in Robot-Assisted Surgery: Challenges and Benefits

Robotic surgery is transforming the current surgical practice, not only by improving the conventional surgical methods but also by introducing innovative robot-enhanced approaches that broaden the capabilities of clinicians. Being mainly of man-machine collaborative type, surgical robots are seen as media that transfer pre- and intra-operative information to the operator and reproduce his/her motion, with appropriate filtering, scaling, or limitation, to physically interact with the patient. The field, however, is far from maturity and, more critically, is still a subject of controversy in medical communities. Limited or absent haptic feedback is reputed to be among reasons that impede further spread of surgical robots. In this paper objectives and challenges of deploying haptic technologies in surgical robotics is discussed and a systematic review is performed on works that have studied the effects of providing haptic information to the users in major branches of robotic surgery. It has been tried to encompass both classical works and the state of the art approaches, aiming at delivering a comprehensive and balanced survey both for researchers starting their work in this field and for the experts