Model-Augmented Haptic Telemanipulation: Concept, Retrospective Overview, and Current Use Cases.

Certain telerobotic applications, including telerobotics in space, pose particularly demanding challenges to both technology and humans. Traditional bilateral telemanipulation approaches often cannot be used in such applications due to technical and physical limitations such as long and varying delays, packet loss, and limited bandwidth, as well as high reliability, precision, and task duration requirements. In order to close this gap, we research model-augmented haptic telemanipulation (MATM) that uses two kinds of models: a remote model that enables shared autonomous functionality of the teleoperated robot, and a local model that aims to generate assistive augmented haptic feedback for the human operator. Several technological methods that form the backbone of the MATM approach have already been successfully demonstrated in accomplished telerobotic space missions. On this basis, we have applied our approach in more recent research to applications in the fields of orbital robotics, telesurgery, caregiving, and telenavigation. In the course of this work, we have advanced specific aspects of the approach that were of particular importance for each respective application, especially shared autonomy, and haptic augmentation. This overview paper discusses the MATM approach in detail, presents the latest research results of the various technologies encompassed within this approach, provides a retrospective of DLR's telerobotic space missions, demonstrates the broad application potential of MATM based on the aforementioned use cases, and outlines lessons learned and open challenges.

[Robotic assistance systems for surgery : Current developments and focus of research]. / Robotische Assistenzsysteme für die Chirurgie : Aktuelle Entwicklungen und Schwerpunkte der Forschung.

As robotic systems are now technically mature and widely available, they also play an increasingly important role in the clinical environment. Thus, numerous robotic assistance systems for diagnosis and therapy have shown their potential for supporting patient care. After a brief review of the history, this article describes currently available robotic assistance systems for surgery, especially those originating in Germany and Europe as well as current focal topics of research. In addition, challenges in this field as well as possibilities for close active and interdisciplinary cooperation between stakeholders from hospitals, industry and science to overcome such challenges are presented.

Motion estimation in beating heart surgery.

Minimally invasive beating-heart surgery offers substantial benefits for the patient, compared to conventional open surgery. Nevertheless, the motion of the heart poses increased requirements to the surgeon. To support the surgeon, algorithms for an advanced robotic surgery system are proposed, which offer motion compensation of the beating heart. This implies the measurement of heart motion, which can be achieved by tracking natural landmarks. In most cases, the investigated affine tracking scheme can be reduced to an efficient block matching algorithm allowing for realtime tracking of multiple landmarks. Fourier analysis of the motion parameters shows two dominant peaks, which correspond to the heart and respiration rates of the patient. The robustness in case of disturbance or occlusion can be improved by specially developed prediction schemes. Local prediction is well suited for the detection of single tracking outliers. A global prediction scheme takes several landmarks into account simultaneously and is able to bridge longer disturbances. As the heart motion is strongly correlated with the patient's electrocardiogram and respiration pressure signal, this information is included in a novel robust multisensor prediction scheme. Prediction results are compared to those of an artificial neural network and of a linear prediction approach, which shows the superior performance of the proposed algorithms.

A virtual-reality-based haptic surgical training system.

To improve training facilities for surgeons, a surgical training system based on virtual reality techniques has been developed. The goal of the developed system is to improve education of surgeons by making the knowledge of expert surgeons directly available to trainees. The system realizes two different approaches: the library and the driving school paradigm. In its current form, the system consists of two modules. The main module combines the virtual reality kernel KISMET, a visual and haptic display, and a database of different operations and/or techniques. The master station is a copy of the input and output facilities of the main module. Both modules communicate by a TCP/ IP-based connection. Initial tests demonstrated the feasibility of the chosen framework. Further developments include the gathering of data not only from virtual reality but also from real operations. Robotic-assisted surgery provides an attractive way of accomplishing this.