The Shape of Damping: Optimizing Damping Coefficients to Improve Transparency on Bilateral Telemanipulation

This thesis presents a novel optimization-based passivity control algorithm for hapticenabled bilateral teleoperation systems involving multiple degrees of freedom. In particular, in the context of energy-bounding control, the contribution focuses on the implementation of a passivity layer for an existing time-domain scheme, ensuring optimal transparency of the interaction along subsets of the environment space which are preponderant for the given task, while preserving the energy bounds required for passivity. The involved optimization problem is convex and amenable to real-time implementation. The effectiveness of the proposed design is validated via an experiment performed on a virtual teleoperated environment. The interplay between transparency and stability is a critical aspect in haptic-enabled bilateral teleoperation control. While it is important to present the user with the true impedance of the environment, destabilizing factors such as time delays, stiff environments, and a relaxed grasp on the master device may compromise the stability and safety of the system. Passivity has been exploited as one of the the main tools for providing sufficient conditions for stable teleoperation in several controller design approaches, such as the scattering algorithm, timedomain passivity control, energy bounding algorithm, and passive set position modulation. In this work it is presented an innovative energy-based approach, which builds upon existing time-domain passivity controllers, improving and extending their effectiveness and functionality. The set of damping coefficients are prioritized in each degree of freedom, the resulting transparency presents a realistic force feedback in comparison to the other directions. Thus, the prioritization takes effect using a quadratic programming algorithm to find the optimal values for the damping. Finally, the energy tanks approach on passivity control is a solution used to ensure stability in a system for robotics bilateral manipulation. The bilateral telemanipulation must maintain the principle of passivity in all moments to preserve the system\u2019s stability. This work presents a brief introduction to haptic devices as a master component on the telemanipulation chain; the end effector in the slave side is a representation of an interactive object within an environment having a force sensor as feedback signal. The whole interface is designed into a cross-platform framework named ROS, where the user interacts with the system. Experimental results are presented

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

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

Haptics-Enabled Teleoperation for Robotics-Assisted Minimally Invasive Surgery

The lack of force feedback (haptics) in robotic surgery can be considered to be a safety risk leading to accidental tissue damage and puncturing of blood vessels due to excessive forces being applied to tissue and vessels or causing inefficient control over the instruments because of insufficient applied force. This project focuses on providing a satisfactory solution for introducing haptic feedback in robotics-assisted minimally invasive surgical (RAMIS) systems. The research addresses several key issues associated with the incorporation of haptics in a master-slave (teleoperated) robotic environment for minimally invasive surgery (MIS). In this project, we designed a haptics-enabled dual-arm (two masters - two slaves) robotic MIS testbed to investigate and validate various single-arm as well as dual-arm teleoperation scenarios. The most important feature of this setup is the capability of providing haptic feedback in all 7 degrees of freedom (DOF) required for RAMIS (3 translations, 3 rotations and pinch motion of the laparoscopic tool). The setup also enables the evaluation of the effect of replacing haptic feedback by other sensory cues such as visual representation of haptic information (sensory substitution) and the hypothesis that surgical outcomes may be improved by substituting or augmenting haptic feedback by such sensory cues

Control of Cooperative Haptics-Enabled Teleoperation Systems with Application to Minimally Invasive Surgery

Robot-Assisted Minimally Invasive Surgical (RAMIS) systems frequently have a structure of cooperative teleoperator systems where multiple master-slave pairs are used to collaboratively execute a task. Although multiple studies indicate that haptic feedback improves the realism of tool-tissue interaction to the surgeon and leads to better performance for surgical procedures, current telesurgical systems typically do not provide force feedback, mainly because of the inherent stability issues. The research presented in this thesis is directed towards the development of control algorithms for force reflecting cooperative surgical teleoperator systems with improved stability and transparency characteristics. In the case of cooperative force reflecting teleoperation over networks, conventional passivity based approaches may have limited applicability due to potentially non-passive slave-slave interactions and irregular communication delays imposed by the network. In this thesis, an alternative small gain framework for the design of cooperative network-based force reflecting teleoperator systems is developed. Using the small gain framework, control algorithms for cooperative force-reflecting teleoperator systems are designed that guarantee stability in the presence of multiple network-induced communication constraints. Furthermore, the design conservatism typically associated with the small-gain approach is eliminated by using the Projection-Based Force Reflection (PBFR) algorithms. Stability results are established for networked cooperative teleoperator systems under different types of force reflection algorithms in the presence of irregular communication delays. The proposed control approach is consequently implemented on a dual-arm (two masters/two slaves) robotic MIS testbed. The testbed consists of two Haptic Wand devices as masters and two PA10-7C robots as the slave manipulators equipped with da Vinci laparoscopic surgical instruments. The performance of the proposed control approach is evaluated in three different cooperative surgical tasks, which are knot tightening, pegboard transfer, and object manipulation. The experimental results obtained indicate that the PBFR algorithms demonstrate statistically significant performance improvement in comparison with the conventional direct force reflection algorithms. One possible shortcoming of using PBFR algorithms is that implementation of these algorithms may lead to attenuation of the high-frequency component of the contact force which is important, in particular, for haptic perception of stiff surfaces. In this thesis, a solution to this problem is proposed which is based on the idea of separating the different frequency bands in the force reflection signal and consequently applying the projection-based principle to the low-frequency component, while reflecting the high-frequency component directly. The experimental results demonstrate that substantial improvement in transient fidelity of the force feedback is achieved using the proposed method without negative effects on the stability of the system

Cutaneous Force Feedback as a Sensory Subtraction Technique in Haptics

A novel sensory substitution technique is presented. Kinesthetic and cutaneous force feedback are substituted by cutaneous feedback (CF) only, provided by two wearable devices able to apply forces to the index finger and the thumb, while holding a handle during a teleoperation task. The force pattern, fed back to the user while using the cutaneous devices, is similar, in terms of intensity and area of application, to the cutaneous force pattern applied to the finger pad while interacting with a haptic device providing both cutaneous and kinesthetic force feedback. The pattern generated using the cutaneous devices can be thought as a subtraction between the complete haptic feedback (HF) and the kinesthetic part of it. For this reason, we refer to this approach as sensory subtraction instead of sensory substitution. A needle insertion scenario is considered to validate the approach. The haptic device is connected to a virtual environment simulating a needle insertion task. Experiments show that the perception of inserting a needle using the cutaneous-only force feedback is nearly indistinguishable from the one felt by the user while using both cutaneous and kinesthetic feedback. As most of the sensory substitution approaches, the proposed sensory subtraction technique also has the advantage of not suffering from stability issues of teleoperation systems due, for instance, to communication delays. Moreover, experiments show that the sensory subtraction technique outperforms sensory substitution with more conventional visual feedback (VF)