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

Position / force control of systems subjected to communicaton delays and interruptions in bilateral teleoperation

Thesis (Master)--Izmir Institute of Technology, Mechanical Engineering, Izmir, 2012Includes bibliographical references (leaves: 65-68)Text in English; Abstract: Turkish and Englishix, 76 leavesTeleoperation technology allows to remotely operate robotic (slave) systems located in hazardous, risky and distant environments. The human operator sends commands through the controller (master) system to execute the tasks from a distance. The operator is provided with necessary (visual, audio or haptic) feedback to accomplish the mission remotely. In bilateral teleoperation, continuous feedback from the remote environment is generated. Thus, the operator can handle the task as if the operator is in the remote environment relying on the relevant feedback. Since teleoperation deals with systems controlled from a distance, time delays and package losses in transmission of information are present. These communication failures affect the human perception and system stability, and thus, the ability of operator to handle the task successfully. The objective of this thesis is to investigate and develop a control algorithm, which utilizes model mediated teleoperation integrating parallel position/force controllers, to compensate for the instability issues and excessive forcing applied to the environment arising from communication failures. Model mediation technique is extended for three-degrees-of-freedom teleoperation and a parallel position/force controller, impedance controller, is integrated in the control algorithm. The proposed control method is experimentally tested by using Matlab Simulink blocksets for real-time experimentation in which haptic desktop devices, Novint Falcon and Phantom Desktop are configured as master and slave subsystems of the bilateral teleoperation. The results of these tests indicate that the stability and passivity of proposed bilateral teleoperation systems are preserved during constant and variable time delays and data losses while the position and force tracking test results provide acceptable performance with bounded errors

Stabilization and control of teleoperation systems with time delays

A control scheme for teleoperation systems with time delay is developed based on the concept of passivity. This control method requires neither detailed knowledge of the manipulator systems nor the mathematical models of the environments, and it is applicable for any time delays. The main contribution of this method is that it is less conservative than the traditional passivity based method. In this method, the passivity controller only operates when the system loses passivity, while in a traditional passivity formulation, the controller works at all times during operation and thus adversely affect the performance of the system.;Using the proposed control scheme, a sub-system is defined that is composed of the communication channel, slave robot and the manipulated environment. This sub system is treated as a one-port network component, and passivity theory is applied to this component to assure stability. The energy flowing into the one-port network, in the form of the control command and the force feedback, is monitored. A passivity regulator is activated to maintain the passivity of the network by modifying the feedback force to the master, and thus adjust the energy exchange between the master and the communication channel.;When this method is applied, only the information at the interface between the master manipulator and the communication channel is collected and observed, there is no need for accurate or detailed knowledge of the structure or timing of the communication channel. The method can make the system lossless regardless of the feedback force, the coordinating force controlling the slave joint motions or the contact force. The approach can stabilize the system regardless of the time delay, discontinuities with environmental contact, or discretization of the physical plant. It will pose no problem when the environmental contact force is directly fed back. The results of this work show that it is advantageous to use the measured environmental force as the feedback, providing superior performance for free motion and more realistic haptic feedback for the operator from the remote environment.;Simulation and experimental results are presented to verify the proposed control scheme

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

Passivity-Based adaptive bilateral teleoperation control for uncertain manipulators without jerk measurements

In this work, we consider the bilateral teleoperation problem of cooperative robotic systems in a Single-Master Multi-Slave (SM/MS) configuration, which is able to perform load transportation tasks in the presence of parametric uncertainty in the robot kinematic and dynamic models. The teleoperation architecture is based on the two-layer approach placed in a hierarchical structure, whose top and bottom layers are responsible for ensuring the transparency and stability properties respectively. The load transportation problem is tackled by using the formation control approach wherein the desired translational velocity and interaction force are provided to the master robot by the user, while the object is manipulated with a bounded constant force by the slave robots. Firstly, we develop an adaptive kinematic-based control scheme based on a composite adaptation law to solve the cooperative control problem for robots with uncertain kinematics. Secondly, the dynamic adaptive control for cooperative robots is implemented by means of a cascade control strategy, which does not require the measurement of the time derivative of force (which requires jerk measurements). The combination of the Lyapunov stability theory and the passivity formalism are used to establish the stability and convergence property of the closed-loop control system. Simulations and experimental results illustrate the performance and feasibility of the proposed control scheme.No presente trabalho, considera-se o problema de teleoperação bilateral de um sistema robótico cooperativo do tipo single-master e multiple-slaves (SM/MS) capaz de realizar tarefas de transporte de carga na presença de incertezas paramétricas no modelo cinemático e dinâmico dos robôs. A arquitetura de teleoperação está baseada na abordagem de duas camadas em estrutura hierárquica, onde as camadas superior e inferior são responsáveis por assegurar as propriedades de transparência e estabilidade respectivamente. O problema de transporte de carga é formulado usando a abordagem de controle de formação onde a velocidade de translação desejada e a força de interação são fornecidas ao robô mestre pelo operador, enquanto o objeto é manipulado pelos robôs escravos com uma força constante limitada. Primeiramente, desenvolve-se um esquema de controle adaptativo cinemático baseado em uma lei de adaptação composta para solucionar o problema de controle cooperativo de robôs com cinemática incerta. Em seguida, o controle adaptativo dinâmico de robôs cooperativos é implementado por meio de uma estratégia de controle em cascata, que não requer a medição da derivada da força (o qual requer a derivada da aceleração ou jerk). A teoria de estabilidade de Lyapunov e o formalismo de passividade são usados para estabelecer as propriedades de estabilidade e a convergência do sistema de controle em malha-fechada. Resultados de simulações numéricas ilustram o desempenho e viabilidade da estratégia de controle proposta

Trust-Based Control of (Semi)Autonomous Mobile Robotic Systems

Despite great achievements made in (semi)autonomous robotic systems, human participa-tion is still an essential part, especially for decision-making about the autonomy allocation of robots in complex and uncertain environments. However, human decisions may not be optimal due to limited cognitive capacities and subjective human factors. In human-robot interaction (HRI), trust is a major factor that determines humans use of autonomy. Over/under trust may lead to dispro-portionate autonomy allocation, resulting in decreased task performance and/or increased human workload. In this work, we develop automated decision-making aids utilizing computational trust models to help human operators achieve a more effective and unbiased allocation. Our proposed decision aids resemble the way that humans make an autonomy allocation decision, however, are unbiased and aim to reduce human workload, improve the overall performance, and result in higher acceptance by a human. We consider two types of autonomy control schemes for (semi)autonomous mobile robotic systems. The first type is a two-level control scheme which includes switches between either manual or autonomous control modes. For this type, we propose automated decision aids via a computational trust and self-confidence model. We provide analytical tools to investigate the steady-state effects of the proposed autonomy allocation scheme on robot performance and human workload. We also develop an autonomous decision pattern correction algorithm using a nonlinear model predictive control to help the human gradually adapt to a better allocation pattern. The second type is a mixed-initiative bilateral teleoperation control scheme which requires mixing of autonomous and manual control. For this type, we utilize computational two-way trust models. Here, mixed-initiative is enabled by scaling the manual and autonomous control inputs with a function of computational human-to-robot trust. The haptic force feedback cue sent by the robot is dynamically scaled with a function of computational robot-to-human trust to reduce humans physical workload. Using the proposed control schemes, our human-in-the-loop tests show that the trust-based automated decision aids generally improve the overall robot performance and reduce the operator workload compared to a manual allocation scheme. The proposed decision aids are also generally preferred and trusted by the participants. Finally, the trust-based control schemes are extended to the single-operator-multi-robot applications. A theoretical control framework is developed for these applications and the stability and convergence issues under the switching scheme between different robots are addressed via passivity based measures

Toward safe and stable time-delayed mobile robot teleoperation through sampling-based path planning

This work proposes a teleoperation architecture for mobile robots in partially unknown environments under the presence of variable time delay. The system is provided with artificial intelligence represented by a probabilistic path planner that, in combination with a prediction module, assists the operator while guaranteeing a collision-free motion. For this purpose, a certain level of autonomy is given to the system. The structure was tested in indoor environments for different kinds of operators. A maximum time delay of 2s was successfully coped with. © 2011 Cambridge University Press

A task learning mechanism for the telerobots

Telerobotic systems have attracted growing attention because of their superiority in the dangerous or unknown interaction tasks. It is very challengeable to exploit such systems to implement complex tasks in an autonomous way. In this paper, we propose a task learning framework to represent the manipulation skill demonstrated by a remotely controlled robot.Gaussian mixture model is utilized to encode and parametrize the smooth task trajectory according to the observations from the demonstrations. After encoding the demonstrated trajectory, a new task trajectory is generated based on the variability information of the learned model. Experimental results have demonstrated the feasibility of the proposed method