The use of laparoscopic and robotic procedures has increased in general surgery. Minimally invasive robotic surgery has made tremendous progress in a relatively short period of time, realizing improvements for both the patient and surgeon. This has led to an increase in the use and development of robotic devices and platforms for general surgery. The purpose of this review is to explore current and emerging surgical robotic technologies in a growing and dynamic environment of research and development. This review explores medical and surgical robotic endoscopic surgery and peripheral technologies currently available or in development. The devices discussed here are specific to general surgery, including laparoscopy, colonoscopy, esophagogastroduodenoscopy, and thoracoscopy. Benefits and limitations of each technology were identified and applicable future directions were described. A number of FDA-approved devices and platforms for robotic surgery were reviewed, including the da Vinci Surgical System, Sensei X Robotic Catheter System, FreeHand 1.2, invendoscopy E200 system, Flex® Robotic System, Senhance, ARES, the Single-Port Instrument Delivery Extended Research (SPIDER), and the NeoGuide Colonoscope. Additionally, platforms were reviewed which have not yet obtained FDA approval including MiroSurge, ViaCath System, SPORT™ Surgical System, SurgiBot, Versius Robotic System, Master and Slave Transluminal Endoscopic Robot, Verb Surgical, Miniature In Vivo Robot, and the Einstein Surgical Robot. The use and demand for robotic medical and surgical platforms is increasing and new technologies are continually being developed. New technologies are increasingly implemented to improve on the capabilities of previously established systems. Future studies are needed to further evaluate the strengths and weaknesses of each robotic surgical device and platform in the operating suite.

Review of emerging surgical robotic technology

The advent of affordable consumer grade RGB‐D cameras has brought about a profound advancement of visual scene reconstruction methods. Both computer graphics and computer vision researchers spend significant effort to develop entirely new algorithms to capture comprehensive shape models of static and dynamic scenes with RGB‐D cameras. This led to significant advances of the state of the art along several dimensions. Some methods achieve very high reconstruction detail, despite limited sensor resolution. Others even achieve real‐time performance, yet possibly at lower quality. New concepts were developed to capture scenes at larger spatial and temporal extent. Other recent algorithms flank shape reconstruction with concurrent material and lighting estimation, even in general scenes and unconstrained conditions. In this state‐of‐the‐art report, we analyze these recent developments in RGB‐D scene reconstruction in detail and review essential related work. We explain, compare, and critically analyze the common underlying algorithmic concepts that enabled these recent advancements. Furthermore, we show how algorithms are designed to best exploit the benefits of RGB‐D data while suppressing their often non‐trivial data distortions. In addition, this report identifies and discusses important open research questions and suggests relevant directions for future work.

State of the Art on 3D Reconstruction with RGB-D Cameras

This paper gives an overview on the torque-controlled humanoid robot TORO, which has evolved from the former DLR Biped. In particular, we describe its mechanical design and dimensioning, its sensors, electronics and computer hardware. Additionally, we give a short introduction to the walking and multi-contact balancing strategies used for TORO.

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Overview of the torque-controlled humanoid robot TORO

In this paper, a statistical approach to fault detection and isolation (FDI) of robot manipulators is presented It is based on a statistical method called partial least squares (PLS) and on the inverse dynamic model of a robot PLS is a well-established linear technique in process control for identifying and monitoring industrial plants Since a robot inverse dynamics can be represented as a linear static model in the dynamical parameters, it is possible to use algorithms and confidence regions developed in statistical decision theory This approach has several advantages with respect to standard FDI modules: It is strictly related to the algorithm used for identifying the dynamical parameters, it does not need to solve at run time a set of nonlinear differential equations, and the design of a nonlinear observer is not required This method has been tested on a PUMA 560 simulator, and results of the simulations are discussed

A PLS-Based Statistical Approach for Fault Detection and Isolation of Robotic Manipulators

Autonomous mobile robots are becoming more prominent in recent time because of their relevance and applications to the world today. Their ability to navigate in an environment without a need for physical or electro-mechanical guidance devices has made it more promising and useful. The use of autonomous mobile robots is emerging in different sectors such as companies, industries, hospital, institutions, agriculture and homes to improve services and daily activities. Due to technology advancement, the demand for mobile robot has increased due to the task they perform and services they render such as carrying heavy objects, monitoring, search and rescue missions, etc. Various studies have been carried out by researchers on the importance of mobile robot, its applications and challenges. This survey paper unravels the current literatures, the challenges mobile robot is being faced with. A comprehensive study on devices/sensors and prevalent sensor fusion techniques developed for tackling issues like localization, estimation and navigation in mobile robot are presented as well in which they are organised according to relevance, strengths and weaknesses. The study therefore gives good direction for further investigation on developing methods to deal with the discrepancies faced with autonomous mobile robot.

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A Review on Challenges of Autonomous Mobile Robot and Sensor Fusion Methods

This work focuses on autonomous surface reconstruction of small-scale objects with a robot and a 3D sensor. The aim is a high-quality surface model allowing for robotic applications such as grasping and manipulation. Our approach comprises the generation of next-best-scan (NBS) candidates and selection criteria, error minimization between scan patches and termination criteria. NBS candidates are iteratively determined by a boundary detection and surface trend estimation of the acquired model. To account for both a fast and high-quality model acquisition, that candidate is selected as NBS, which maximizes a utility function that integrates an exploration and a mesh-quality component. The modeling and scan planning methods are evaluated on an industrial robot with a high-precision laser striper system. While performing the new laser scan, data are integrated on-the-fly into both, a triangle mesh and a probabilistic voxel space. The efficiency of the system in fast acquisition of high-quality 3D surface models is proven with different cultural heritage, household and industrial objects.

Efficient next-best-scan planning for autonomous 3D surface reconstruction of unknown objects

Research on humanoid robots for use in servicing tasks, e.g. fetching and delivery, attracts steadily more interest. With “Rollin' Justin” a mobile robotic system and research platform is presented that allows sophisticated control algorithms and dexterous manipulation. This video gives an overview of the mobile humanoid robotic system “Rollin' Justin” with special emphasis on mechanical design features, control issues and high-level system capabilities such as human robot interaction.

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Rollin' Justin - Mobile platform with variable base

This video presents the in-house developed DLR MiroSurge robotic system for surgery. As shown, the system is suitable for both minimally invasive and open surgery. Essential part of the system is the MIRO robot: The soft robotics feature enables intuitive interaction with the robot.

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The DLR MiroSurge - A robotic system for surgery

We present a next-best-scan (NBS) planning approach for autonomous 3D modeling. The system successively completes a 3D model from complex shaped objects by iteratively selecting a NBS based on previously acquired data. For this purpose, new range data is accumulated in-the-loop into a 3D surface (streaming reconstruction) and new continuous scan paths along the estimated surface trend are generated. Further, the space around the object is explored using a probabilistic exploration approach that considers sensor uncertainty. This allows for collision free path planning in order to completely scan unknown objects. For each scan path, the expected information gain is determined and the best path is selected as NBS. The presented NBS approach is tested with a laser striper system, attached to an industrial robot. The results are compared to state-of-the-art next-best-view methods. Our results show promising performance with respect to completeness, quality and scan time.

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Next-best-scan planning for autonomous 3D modeling

This work is focused on global registration of surface models such as homogeneous triangle meshes and point clouds. The investigated approach utilizes feature descriptors in order to assign correspondences between the data sets and to reduce complexity by considering only characteristic feature points. It is based on the decomposability of rigid motions into a rotation and a translation. The space of rotations is searched with a particle filter and scoring is performed by looking for clusters in the resulting sets of translations. We use features computed from homogeneous triangle meshes and point clouds that require low computation time. A major advantage of the approach proves to be the possible consideration of prior knowledge about the relative orientation. This is especially important when high noise levels produce deteriorated features that are hard to match correctly. Comparisons to existing algorithms show the method's competitiveness, and results in robotic applications with different sensor types are presented.

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Christian Rink

Papers

Efficient next-best-scan planning for autonomous 3D surface reconstruction of unknown objects

Rollin' Justin - Mobile platform with variable base

The DLR MiroSurge - A robotic system for surgery

Next-best-scan planning for autonomous 3D modeling

Feature based particle filter registration of 3D surface models and its application in robotics