A review on manipulation skill acquisition through teleoperation-based learning from demonstration

Manipulation skill learning and generalization have gained increasing attention due to the wide applications of robot manipulators and the spurt of robot learning techniques. Especially, the learning from demonstration method has been exploited widely and successfully in the robotic community, and it is regarded as a promising direction to realize the manipulation skill learning and generalization. In addition to the learning techniques, the immersive teleoperation enables the human to operate a remote robot with an intuitive interface and achieve the telepresence. Thus, it is a promising way to transfer manipulation skills from humans to robots by combining the learning methods and the teleoperation, and adapting the learned skills to different tasks in new situations. This review, therefore, aims to provide an overview of immersive teleoperation for skill learning and generalization to deal with complex manipulation tasks. To this end, the key technologies, e.g. manipulation skill learning, multimodal interfacing for teleoperation and telerobotic control, are introduced. Then, an overview is given in terms of the most important applications of immersive teleoperation platform for robot skill learning. Finally, this survey discusses the remaining open challenges and promising research topics

Robot manipulator skill learning and generalising through teleoperation

Robot manipulators have been widely used for simple repetitive, and accurate tasks in industrial plants, such as pick and place, assembly and welding etc., but it is still hard to deploy in human-centred environments for dexterous manipulation tasks, such as medical examination and robot-assisted healthcare. These tasks are not only related to motion planning and control but also to the compliant interaction behaviour of robots, e.g. motion control, force regulation and impedance adaptation simultaneously under dynamic and unknown environments. Recently, with the development of collaborative robotics (cobots) and machine learning, robot skill learning and generalising have attained increasing attention from robotics, machine learning and neuroscience communities. Nevertheless, learning complex and compliant manipulation skills, such as manipulating deformable objects, scanning the human body and folding clothes, is still challenging for robots. On the other hand, teleoperation, also namely remote operation or telerobotics, has been an old research area since 1950, and there have been a number of applications such as space exploration, telemedicine, marine vehicles and emergency response etc. One of its advantages is to combine the precise control of robots with human intelligence to perform dexterous and safety-critical tasks from a distance. In addition, telepresence allows remote operators could feel the actual interaction between the robot and the environment, including the vision, sound and haptic feedback etc. Especially under the development of various augmented reality (AR), virtual reality (VR) and wearable devices, intuitive and immersive teleoperation have received increasing attention from robotics and computer science communities. Thus, various human-robot collaboration (HRC) interfaces based on the above technologies were developed to integrate robot control and telemanipulation by human operators for robot skills learning from human beings. In this context, robot skill learning could benefit teleoperation by automating repetitive and tedious tasks, and teleoperation demonstration and interaction by human teachers also allow the robot to learn progressively and interactively. Therefore, in this dissertation, we study human-robot skill transfer and generalising through intuitive teleoperation interfaces for contact-rich manipulation tasks, including medical examination, manipulating deformable objects, grasping soft objects and composite layup in manufacturing. The introduction, motivation and objectives of this thesis are introduced in Chapter 1. In Chapter 2, a literature review on manipulation skills acquisition through teleoperation is carried out, and the motivation and objectives of this thesis are discussed subsequently. Overall, the main contents of this thesis have three parts: Part 1 (Chapter 3) introduces the development and controller design of teleoperation systems with multimodal feedback, which is the foundation of this project for robot learning from human demonstration and interaction. In Part 2 (Chapters 4, 5, 6 and 7), we studied primitive skill library theory, behaviour tree-based modular method, and perception-enhanced method to improve the generalisation capability of learning from the human demonstrations. And several applications were employed to evaluate the effectiveness of these methods.In Part 3 (Chapter 8), we studied the deep multimodal neural networks to encode the manipulation skill, especially the multimodal perception information. This part conducted physical experiments on robot-assisted ultrasound scanning applications.Chapter 9 summarises the contributions and potential directions of this thesis. Keywords: Learning from demonstration; Teleoperation; Multimodal interface; Human-in-the-loop; Compliant control; Human-robot interaction; Robot-assisted sonography

A continuum robotic platform for endoscopic non-contact laser surgery: design, control, and preclinical evaluation

The application of laser technologies in surgical interventions has been accepted in the clinical domain due to their atraumatic properties. In addition to manual application of fibre-guided lasers with tissue contact, non-contact transoral laser microsurgery (TLM) of laryngeal tumours has been prevailed in ENT surgery. However, TLM requires many years of surgical training for tumour resection in order to preserve the function of adjacent organs and thus preserve the patient’s quality of life. The positioning of the microscopic laser applicator outside the patient can also impede a direct line-of-sight to the target area due to anatomical variability and limit the working space. Further clinical challenges include positioning the laser focus on the tissue surface, imaging, planning and performing laser ablation, and motion of the target area during surgery. This dissertation aims to address the limitations of TLM through robotic approaches and intraoperative assistance. Although a trend towards minimally invasive surgery is apparent, no highly integrated platform for endoscopic delivery of focused laser radiation is available to date. Likewise, there are no known devices that incorporate scene information from endoscopic imaging into ablation planning and execution. For focusing of the laser beam close to the target tissue, this work first presents miniaturised focusing optics that can be integrated into endoscopic systems. Experimental trials characterise the optical properties and the ablation performance. A robotic platform is realised for manipulation of the focusing optics. This is based on a variable-length continuum manipulator. The latter enables movements of the endoscopic end effector in five degrees of freedom with a mechatronic actuation unit. The kinematic modelling and control of the robot are integrated into a modular framework that is evaluated experimentally. The manipulation of focused laser radiation also requires precise adjustment of the focal position on the tissue. For this purpose, visual, haptic and visual-haptic assistance functions are presented. These support the operator during teleoperation to set an optimal working distance. Advantages of visual-haptic assistance are demonstrated in a user study. The system performance and usability of the overall robotic system are assessed in an additional user study. Analogous to a clinical scenario, the subjects follow predefined target patterns with a laser spot. The mean positioning accuracy of the spot is 0.5 mm. Finally, methods of image-guided robot control are introduced to automate laser ablation. Experiments confirm a positive effect of proposed automation concepts on non-contact laser surgery.Die Anwendung von Lasertechnologien in chirurgischen Interventionen hat sich aufgrund der atraumatischen Eigenschaften in der Klinik etabliert. Neben manueller Applikation von fasergeführten Lasern mit Gewebekontakt hat sich die kontaktfreie transorale Lasermikrochirurgie (TLM) von Tumoren des Larynx in der HNO-Chirurgie durchgesetzt. Die TLM erfordert zur Tumorresektion jedoch ein langjähriges chirurgisches Training, um die Funktion der angrenzenden Organe zu sichern und damit die Lebensqualität der Patienten zu erhalten. Die Positionierung des mikroskopis chen Laserapplikators außerhalb des Patienten kann zudem die direkte Sicht auf das Zielgebiet durch anatomische Variabilität erschweren und den Arbeitsraum einschränken. Weitere klinische Herausforderungen betreffen die Positionierung des Laserfokus auf der Gewebeoberfläche, die Bildgebung, die Planung und Ausführung der Laserablation sowie intraoperative Bewegungen des Zielgebietes. Die vorliegende Dissertation zielt darauf ab, die Limitierungen der TLM durch robotische Ansätze und intraoperative Assistenz zu adressieren. Obwohl ein Trend zur minimal invasiven Chirurgie besteht, sind bislang keine hochintegrierten Plattformen für die endoskopische Applikation fokussierter Laserstrahlung verfügbar. Ebenfalls sind keine Systeme bekannt, die Szeneninformationen aus der endoskopischen Bildgebung in die Ablationsplanung und -ausführung einbeziehen. Für eine situsnahe Fokussierung des Laserstrahls wird in dieser Arbeit zunächst eine miniaturisierte Fokussieroptik zur Integration in endoskopische Systeme vorgestellt. Experimentelle Versuche charakterisieren die optischen Eigenschaften und das Ablationsverhalten. Zur Manipulation der Fokussieroptik wird eine robotische Plattform realisiert. Diese basiert auf einem längenveränderlichen Kontinuumsmanipulator. Letzterer ermöglicht in Kombination mit einer mechatronischen Aktuierungseinheit Bewegungen des Endoskopkopfes in fünf Freiheitsgraden. Die kinematische Modellierung und Regelung des Systems werden in ein modulares Framework eingebunden und evaluiert. Die Manipulation fokussierter Laserstrahlung erfordert zudem eine präzise Anpassung der Fokuslage auf das Gewebe. Dafür werden visuelle, haptische und visuell haptische Assistenzfunktionen eingeführt. Diese unterstützen den Anwender bei Teleoperation zur Einstellung eines optimalen Arbeitsabstandes. In einer Anwenderstudie werden Vorteile der visuell-haptischen Assistenz nachgewiesen. Die Systemperformanz und Gebrauchstauglichkeit des robotischen Gesamtsystems werden in einer weiteren Anwenderstudie untersucht. Analog zu einem klinischen Einsatz verfolgen die Probanden mit einem Laserspot vorgegebene Sollpfade. Die mittlere Positioniergenauigkeit des Spots beträgt dabei 0,5 mm. Zur Automatisierung der Ablation werden abschließend Methoden der bildgestützten Regelung vorgestellt. Experimente bestätigen einen positiven Effekt der Automationskonzepte für die kontaktfreie Laserchirurgie

Graduate course catalog (Florida International University). [2015-2016]

This catalog contains a description of the various policies, graduate programs, degree requirements, and course offerings at Florida International University during the 2015-2016 academic year.https://digitalcommons.fiu.edu/catalogs/1067/thumbnail.jp