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

Kinesthetic Haptics Sensing and Discovery with Bilateral Teleoperation Systems

In the mechanical engineering field of robotics, bilateral teleoperation is a classic but still increasing research topic. In bilateral teleoperation, a human operator moves the master manipulator, and a slave manipulator is controlled to follow the motion of the master in a remote, potentially hostile environment. This dissertation focuses on kinesthetic perception analysis in teleoperation systems. Design of the controllers of the systems is studied as the influential factor of this issue. The controllers that can provide different force tracking capability are compared using the same experimental protocol. A 6 DOF teleoperation system is configured as the system testbed. An innovative master manipulator is developed and a 7 DOF redundant manipulator is used as the slave robot. A singularity avoidance inverse kinematics algorithm is developed to resolve the redundancy of the slave manipulator. An experimental protocol is addressed and three dynamics attributes related to kineshtetic feedback are investigated: weight, center of gravity and inertia. The results support our hypothesis: the controller that can bring a better force feedback can improve the performance in the experiments

Control of Networked Robotic Systems

With the infrastructure of ubiquitous networks around the world, the study of robotic systems over communication networks has attracted widespread attention. This area is denominated as networked robotic systems. By exploiting the fruitful technological developments in networking and computing, networked robotic systems are endowed with potential and capabilities for several applications. Robots within a network are capable of connecting with control stations, human operators, sensors, and other robots via digital communication over possibly noisy channels/media. The issues of time delays in communication and data losses have emerged as a pivotal issue that have stymied practical deployment. The aim of this dissertation is to develop control algorithms and architectures for networked robotic systems that guarantee stability with improved overall performance in the presence of time delays in communication. The first topic addressed in this dissertation is controlled synchronization that is utilized for networked robotic systems to achieve collective behaviors. Exploiting passivity property of individual robotic systems, the proposed control schemes and interconnections are shown to ensure stability and convergence of synchronizing errors. The robustness of the control algorithms to constant and time-varying communication delays is also studied. In addition to time delays, the number of communication links, which prevents scalability of networked robotic systems, is another challenging issue. Thus, a synchronizing control with practically feasible constraints of network topology is developed. The problem of networked robotic systems interacting with human operators is then studied subsequently. This research investigates a teleoperation system with heterogeneous robots under asymmetric and unknown communication delays. Sub-task controllers are proposed for redundant slave robot to autonomously achieve additional tasks, such as singularity avoidance, joint angle limits, and collision avoidance. The developed control algorithms can enhance the efficiency of teleoperation systems, thereby ameliorating the performance degradation due to cognitive limitations of human operator and incomplete information about the environment. Compared to traditional robotic systems, control of robotic manipulators over networks has significant advantages; for example, increased flexibility and ease of maintenance. With the utilization of scattering variables, this research demonstrates that transmitting scattering variables over delayed communications can stabilize an otherwise unstable system. An architecture utilizing delayed position feedback in conjunction with scattering variables is developed for the case of time-varying communication delays. The proposed control architecture improves tracking performance and stabilizes robotic manipulators with input-output communication delays. The aforementioned control algorithms and architectures for networked robotic systems are validated via numerical examples and experiments

Human to robot hand motion mapping methods: review and classification

In this article, the variety of approaches proposed in literature to address the problem of mapping human to robot hand motions are summarized and discussed. We particularly attempt to organize under macro-categories the great quantity of presented methods, that are often difficult to be seen from a general point of view due to different fields of application, specific use of algorithms, terminology and declared goals of the mappings. Firstly, a brief historical overview is reported, in order to provide a look on the emergence of the human to robot hand mapping problem as a both conceptual and analytical challenge that is still open nowadays. Thereafter, the survey mainly focuses on a classification of modern mapping methods under six categories: direct joint, direct Cartesian, taskoriented, dimensionality reduction based, pose recognition based and hybrid mappings. For each of these categories, the general view that associates the related reported studies is provided, and representative references are highlighted. Finally, a concluding discussion along with the authors’ point of view regarding future desirable trends are reported.This work was supported in part by the European Commission’s Horizon 2020 Framework Programme with the project REMODEL under Grant 870133 and in part by the Spanish Government under Grant PID2020-114819GB-I00.Peer ReviewedPostprint (published version

Towards Reuse and Recycling of Lithium-ion Batteries: Tele-robotics for Disassembly of Electric Vehicle Batteries

Disassembly of electric vehicle batteries is a critical stage in recovery, recycling and re-use of high-value battery materials, but is complicated by limited standardisation, design complexity, compounded by uncertainty and safety issues from varying end-of-life condition. Telerobotics presents an avenue for semi-autonomous robotic disassembly that addresses these challenges. However, it is suggested that quality and realism of the user's haptic interactions with the environment is important for precise, contact-rich and safety-critical tasks. To investigate this proposition, we demonstrate the disassembly of a Nissan Leaf 2011 module stack as a basis for a comparative study between a traditional asymmetric haptic-'cobot' master-slave framework and identical master and slave cobots based on task completion time and success rate metrics. We demonstrate across a range of disassembly tasks a time reduction of 22%-57% is achieved using identical cobots, yet this improvement arises chiefly from an expanded workspace and 1:1 positional mapping, and suffers a 10-30% reduction in first attempt success rate. For unbolting and grasping, the realism of force feedback was comparatively less important than directional information encoded in the interaction, however, 1:1 force mapping strengthened environmental tactile cues for vacuum pick-and-place and contact cutting tasks.Comment: 21 pages, 12 figures, Submitted to Frontiers in Robotics and AI; Human-Robot Interactio