Manipulation monitoring and robot intervention in complex manipulation sequences

Compared to machines, humans are intelligent and dexterous; they are indispensable for many complex tasks in areas such as flexible manufacturing or scientific experimentation. However, they are also subject to fatigue and inattention, which may cause errors. This motivates automated monitoring systems that verify the correct execution of manipulation sequences. To be practical, such a monitoring system should not require laborious programming.Peer ReviewedPostprint (author's final draft

Using Surfaces and Surface Relations in an Early Cognitive Vision System

The final publication is available at Springer via http://dx.doi.org/10.1007/s00138-015-0705-yWe present a deep hierarchical visual system with two parallel hierarchies for edge and surface information. In the two hierarchies, complementary visual information is represented on different levels of granularity together with the associated uncertainties and confidences. At all levels, geometric and appearance information is coded explicitly in 2D and 3D allowing to access this information separately and to link between the different levels. We demonstrate the advantages of such hierarchies in three applications covering grasping, viewpoint independent object representation, and pose estimation.European Community’s Seventh Framework Programme FP7/IC

Robot Assisted Electrical Impedance Tomography System for Minimally Invasive Surgery

This study presents the development of a robot assisted electrical impedance scanning system able to reconstruct Electrical Impedance Tomography (EIT) during surgical inspection. This system can be directly applied on most existing minimally invasive surgical robots without introducing additional sensor probes to the operating site or modifying the existing surgical tools. By positioning two robotic forceps as electrodes to several positions on the tissue surface and performing electrical measurements, the system is able to obtain electrical information and use them for reconstructing the conductivity distribution using the EIT algorithm. This paper describes the system construction, sensing pattern and reconstruction algorithm in detail. In addition, the developed system is optimized using finite element simulation and evaluated through two realistic experiments. The generated EIT images are able to show the location of the non-homogeneous structure from the surrounding tissue effectively. These results demonstrate the great potential of the proposed system to assist surgeons in detecting subsurface target area of interest

Robot-Assisted Electrical Impedance Scanning system for 2D Electrical Impedance Tomography tissue inspection

The electrical impedance tomography (EIT) technology is an important medical imaging approach to show the electrical characteristics and the homogeneity of a tissue region noninvasively. Recently, this technology has been introduced to the Robot Assisted Minimally Invasive Surgery (RAMIS) for assisting the detection of surgical margin with relevant clinical benefits. Nevertheless, most EIT technologies are based on a fixed multiple-electrodes probe which limits the sensing flexibility and capability significantly. In this study, we present a method for acquiring the EIT measurements during a RAMIS procedure using two already existing robotic forceps as electrodes. The robot controls the forceps tips to a series of predefined positions for injecting excitation current and measuring electric potentials. Given the relative positions of electrodes and the measured electric potentials, the spatial distribution of electrical conductivity in a section view can be reconstructed. Realistic experiments are designed and conducted to simulate two tasks: subsurface abnormal tissue detection and surgical margin localization. According to the reconstructed images, the system is demonstrated to display the location of the abnormal tissue and the contrast of the tissues' conductivity with an accuracy suitable for clinical applications

An Electrical Bioimpedance Scanning System for Subsurface Tissue Detection in Robot Assisted Minimally Invasive Surgery

In Robot Assisted Minimally Invasive Surgery, discriminating critical subsurface structures is essential to make the surgical procedure safer and more efficient. In this paper, a novel robot assisted electrical bio-impedance scanning (RAEIS) system is developed and validated using a series of experiments. The proposed system constructs a tri-polar sensing configuration for tissue homogeneity inspection. Specifically, two robotic forceps are used as electrodes for applying electric current and measuring reciprocal voltages relative to a ground electrode which is placed distal from the measuring site. Compared to existing electrical bioimpedance sensing technology, the proposed system is able to use miniaturized electrodes to measure a site flexibly with enhanced subsurfacial detection capability. This paper presents the concept, the modeling of the sensing method, the hardware design, and the system calibration. Subsequently, a series of experiments are conducted for system evaluation including finite element simulation, saline solution bath experiments and experiments based on ex vivo animal tissues. The experimental results demonstrate that the proposed system can measure the resistivity of the material with high accuracy, and detect a subsurface non-homogeneous object with 100% success rate. The proposed parameters estimation algorithm is able to approximate the resistivity and the depth of the subsurface object effectively with one fast scanning

Robot assisted electrical impedance scanning for tissue bioimpedance spectroscopy measurement

Intraoperative tissue identification is important and frequently required in modern surgical approaches for guiding operation. For this purpose, a novel robot assisted sensing system equipped with a wide-band impedance spectroscope is developed. Without introducing an external sensor probe to the operating site, the proposed system incorporates two robotic instruments for electric current excitation and voltage measurement. Based on the developed measurement strategy and algorithm, the electrical conductivity and permittivity of the tissue region can be calculated. Experiments based on simulation, salines and ex-vivo tissue phantoms are conducted. The experimental results demonstrate that the proposed system has a high measurement accuracy (≥97%). Through a simple support vector machine, a 100% accuracy is achieved for identifying five different tissues. Given the convincing results, the presented sensing system shows great potential in offering effective, fast, and safe tissue inspection