Passive Control Architectures for Collaborative Virtual Haptic Interaction and Bilateral Teleoperation over Unreliable Packet-Switched Digital Network

This PhD dissertation consists of two major parts: collaborative haptic interaction (CHI) and bilateral teleoperation over the Internet. For the CHI, we propose a novel hybrid peer-to-peer (P2P) architecture including the shared virtual environment (SVE) simulation, coupling between the haptic device and VE, and P2P synchronization control among all VE copies. This framework guarantees the interaction stability for all users with general unreliable packet-switched communication network which is the most challenging problem for CHI control framework design. This is achieved by enforcing our novel \emph{passivity condition} which fully considers time-varying non-uniform communication delays, random packet loss/swapping/duplication for each communication channel. The topology optimization method based on graph algebraic connectivity is also developed to achieve optimal performance under the communication bandwidth limitation. For validation, we implement a four-user collaborative haptic system with simulated unreliable packet-switched network connections. Both the hybrid P2P architecture design and the performance improvement due to the topology optimization are verified. In the second part, two novel hybrid passive bilateral teleoperation control architectures are proposed to address the challenging stability and performance issues caused by the general Internet communication unreliability (e.g. varying time delay, packet loss, data duplication, etc.). The first method--Direct PD Coupling (DPDC)--is an extension of traditional PD control to the hybrid teleoperation system. With the assumption that the Internet communication unreliability is upper bounded, the passive gain setting condition is derived and guarantees the interaction stability for the teleoperation system which interacts with unknown/unmodeled passive human and environment. However, the performance of DPDC degrades drastically when communication unreliability is severe because its feasible gain region is limited by the device viscous damping. The second method--Virtual Proxy Based PD Coupling (VPDC)--is proposed to improve the performance while providing the same interaction stability. Experimental and quantitative comparisons between DPDC and VPDC are conducted, and both interaction stability and performance difference are validated

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

Posture-Dependent Projection-Based Force Reflection Algorithms for Bilateral Teleoperators

It was previously established that the projection-based force reflection (PBFR) algorithms improve the overall stability of a force reflecting teleoperation system. The idea behind the PBFR algorithms is to identify the component of the reflected force which is compensated by interaction with the operator\u27s hand, and subsequently attenuate the residual component of the reflected force. If there is no a priori information regarding the behaviour of the human operator, the PBFR gain is selected equal to sufficiently small constant in order to guarantee stability for a wide range of human operator responses. Small PBRF gains, however, may deteriorate the transparency of a teleoperator system. In this thesis, a new method for selecting the PBFR gain is introduced which depends on human postures. Using an online human posture estimation, the introduced posture-dependent PBFR algorithm has been applied to a teleoperation system with force feedback. It is experimentally demonstrated that the developed method for selection of the PBFR gain based on human postures improves the transparency of the teleoperator system while the stability is preserved. Finally, preliminary results that deal with an extension of the developed methods towards a more realistic model of the human arm with 4 degrees of freedom and three dimensional movements are presented

Improved Stability of Haptic Human-Robot Interfaces using Measurement of Human Arm Stiffness

Copyright © Taylor and FrancisDOI: http://dx.doi.org/10.1080/01691864.2014.900162Necessary physical contact between an operator and a force feedback haptic device creates a coupled system consisting of human and machine. This contact, combined with the natural human tendency to increase arm stiffness to attempt to stabilize its motion, can reduce the stability of the system. This paper proposes a method to increase stability on demand while maintaining speed and performance. Operator arm stiffness is not directly measurable, so controllers cannot typically account for this issue. The causes of arm end-point stiffness are examined as related to system stability, and a method for estimating changes in arm stiffness based on arm muscle activity was designed to provide a robotic controller with additional information about the operator. This was accomplished using electromyograms (EMGs) to measure muscle activities and estimating the level of arm stiffness, which was used to adjust the dynamic characteristics of an impedance controller. To support this design, the correlation between EMGs and arm stiffness was validated experimentally. Further experiments characterized the effects of the designed system on operator performance. This showed increased stability and faster, more accurate movements using the compensating system. Such a system could be used in many applications, including force assisting devices in industrial facilities

Output Feedback Bilateral Teleoperation with Force Estimation in the Presence of Time Delays

This thesis presents a novel bilateral teleoperation algorithm for n degree of freedom nonlinear manipulators connected through time delays. Teleoperation has many practical uses, as there are many benefits that come from being able to operate machines from a distance. For instance, the ability to send a remote controlled robotic vehicle into a hazardous environment can be a great asset in many industrial applications. As well, the field of remote medicine can benefit from these technologies. A highly skilled surgeon could perform surgery on a patient who is located in another city, or even country. Earth to space operations and deep sea exploration are other areas where teleoperation is quite useful. Central to the approach presented in this work is the use of second order sliding mode unknown input observers for estimating the external forces acting on the manipulators. The use of these observers removes the need for both velocity and force sensors, leading to a lower cost hardware setup that provides all of the advantages of a position-force teleoperation algorithm. Stability results for this new algorithm are presented for several cases. Stability of each of the master and slave sides of the teleoperation system is demonstrated, showing that the master and slave are both stabilized by their respective controllers when the unknown input observers are used for state and force estimation. Additionally, closed loop stability results for the teleoperation system connected to a variety of slave side environments are presented. Delay-independent stability results for a linear spring-damper environment as well as a general finite-gain stable nonlinear environment are given. Delay-dependent stability results for the case where the slave environment is a liner spring-damper and the delays are commensurate are also presented. As well, stability results for the closed loop under the assumption that the human operator is modeled as a finite-gain stable nonlinear environment are given. Following the theoretical presentation, numerical simulations illustrating the algorithm are presented, and experimental results verifying the practical application of the approach are given

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