Efficient 3D Segmentation, Registration and Mapping for Mobile Robots

Sometimes simple is better! For certain situations and tasks, simple but robust methods can achieve the same or better results in the same or less time than related sophisticated approaches. In the context of robots operating in real-world environments, key challenges are perceiving objects of interest and obstacles as well as building maps of the environment and localizing therein. The goal of this thesis is to carefully analyze such problem formulations, to deduce valid assumptions and simplifications, and to develop simple solutions that are both robust and fast. All approaches make use of sensors capturing 3D information, such as consumer RGBD cameras. Comparative evaluations show the performance of the developed approaches. For identifying objects and regions of interest in manipulation tasks, a real-time object segmentation pipeline is proposed. It exploits several common assumptions of manipulation tasks such as objects being on horizontal support surfaces (and well separated). It achieves real-time performance by using particularly efficient approximations in the individual processing steps, subsampling the input data where possible, and processing only relevant subsets of the data. The resulting pipeline segments 3D input data with up to 30Hz. In order to obtain complete segmentations of the 3D input data, a second pipeline is proposed that approximates the sampled surface, smooths the underlying data, and segments the smoothed surface into coherent regions belonging to the same geometric primitive. It uses different primitive models and can reliably segment input data into planes, cylinders and spheres. A thorough comparative evaluation shows state-of-the-art performance while computing such segmentations in near real-time. The second part of the thesis addresses the registration of 3D input data, i.e., consistently aligning input captured from different view poses. Several methods are presented for different types of input data. For the particular application of mapping with micro aerial vehicles where the 3D input data is particularly sparse, a pipeline is proposed that uses the same approximate surface reconstruction to exploit the measurement topology and a surface-to-surface registration algorithm that robustly aligns the data. Optimization of the resulting graph of determined view poses then yields globally consistent 3D maps. For sequences of RGBD data this pipeline is extended to include additional subsampling steps and an initial alignment of the data in local windows in the pose graph. In both cases, comparative evaluations show a robust and fast alignment of the input data

Fast 3D Perception for Collision Avoidance and SLAM in Domestic Environments

Electronics engineerin

Chapter Fast 3D Perception for Collision Avoidance and SLAM in Domestic Environments

Electronics engineerin

Teleoperated visual inspection and surveillance with unmanned ground and aerial vehicles,” Int

Abstract—This paper introduces our robotic system named UGAV (Unmanned Ground-Air Vehicle) consisting of two semi-autonomous robot platforms, an Unmanned Ground Vehicle (UGV) and an Unmanned Aerial Vehicles (UAV). The paper focuses on three topics of the inspection with the combined UGV and UAV: (A) teleoperated control by means of cell or smart phones with a new concept of automatic configuration of the smart phone based on a RKI-XML description of the vehicles control capabilities, (B) the camera and vision system with the focus to real time feature extraction e.g. for the tracking of the UAV and (C) the architecture and hardware of the UAV

RoboCup@Home: Analysis and results of evolving competitions for domestic and service robots

Scientific competitions are becoming more common in many research areas of artificial intelligence and robotics, since they provide a shared testbed for comparing different solutions and enable the exchange of research results. Moreover, they are interesting for general audiences and industries. Currently, many major research areas in artificial intelligence and robotics are organizing multiple-year competitions that are typically associated with scientific conferences. One important aspect of such competitions is that they are organized for many years. This introduces a temporal evolution that is interesting to analyze. However, the problem of evaluating a competition over many years remains unaddressed. We believe that this issue is critical to properly fuel changes over the years and measure the results of these decisions. Therefore, this article focuses on the analysis and the results of evolving competitions. In this article, we present the RoboCup@Home competition, which is the largest worldwide competition for domestic service robots, and evaluate its progress over the past seven years. We show how the definition of a proper scoring system allows for desired functionalities to be related to tasks and how the resulting analysis fuels subsequent changes to achieve general and robust solutions implemented by the teams. Our results show not only the steadily increasing complexity of the tasks that RoboCup@Home robots can solve but also the increased performance for all of the functionalities addressed in the competition. We believe that the methodology used in RoboCup@Home for evaluating competition advances and for stimulating changes can be applied and extended to other robotic competitions as well as to multi-year research projects involving Artificial Intelligence and Robotics

Measles Virus Infection in a Transgenic Model Virus-Induced Immunosuppression and Central Nervous System Disease

AbstractMeasles virus (MV) infects 40 million persons and kills one million per year primarily by suppressing the immune system and afflicting the central nervous system (CNS). The lack of a suitable small animal model has impeded progress of understanding how MV causes disease and the development of novel therapies and improved vaccines. We tested a transgenic mouse line in which expression of the MV receptor CD46 closely mimicked the location and amount of CD46 found in humans. Virus replicated in and was recovered from these animals' immune systems and was associated with suppression of humoral and cellular immune responses. Infectious virus was recovered from the CNS, replicated primarily in neurons, and spread to distal sites presumably by fast axonal transport. Thus, a small animal model is available for analysis of MV pathogenesis

Retrospective, observational study in patients receiving a dexamethasone intravitreal implant 0.7 mg for macular oedema secondary to retinal vein occlusion

PURPOSE To retrospectively evaluate the re-injection interval, efficacy and safety of dexamethasone (DEX) intravitreal implant 0.7 mg in the treatment of macular oedema (ME) due to retinal vein occlusion (RVO) in Germany in 2009-2012. METHODS Retrospective, multicentre, anonymised observational study of data collected from the first DEX implant 0.7 mg injection through 3-6 months following the last injection. Data were included if the patient was \textgreater18 years old, had a diagnosis of ME secondary to branch or central RVO, and received at least 2 DEX implant 0.7 mg injections during routine practice. RESULTS Data from 87 patients were analysed. Mean time to re-injection between first and second treatments was 5.03 months in the total RVO population, and 5.46 and 4.52 months for the branch and central RVO subpopulations, respectively. An intraocular pressure increase of \textgreater25 mm Hg was recorded in 20% of patients, and 34% of patients began treatment with anti-glaucoma medication, but surgery was not needed for this condition. CONCLUSIONS DEX implant 0.7 mg was found to be well tolerated and effective with repeat treatments in clinical practice