Real-time on-board obstacle avoidance for UAVs based on embedded stereo vision

In order to improve usability and safety, modern unmanned aerial vehicles (UAVs) are equipped with sensors to monitor the environment, such as laser-scanners and cameras. One important aspect in this monitoring process is to detect obstacles in the flight path in order to avoid collisions. Since a large number of consumer UAVs suffer from tight weight and power constraints, our work focuses on obstacle avoidance based on a lightweight stereo camera setup. We use disparity maps, which are computed from the camera images, to locate obstacles and to automatically steer the UAV around them. For disparity map computation we optimize the well-known semi-global matching (SGM) approach for the deployment on an embedded FPGA. The disparity maps are then converted into simpler representations, the so called U-/V-Maps, which are used for obstacle detection. Obstacle avoidance is based on a reactive approach which finds the shortest path around the obstacles as soon as they have a critical distance to the UAV. One of the fundamental goals of our work was the reduction of development costs by closing the gap between application development and hardware optimization. Hence, we aimed at using high-level synthesis (HLS) for porting our algorithms, which are written in C/C++, to the embedded FPGA. We evaluated our implementation of the disparity estimation on the KITTI Stereo 2015 benchmark. The integrity of the overall realtime reactive obstacle avoidance algorithm has been evaluated by using Hardware-in-the-Loop testing in conjunction with two flight simulators.Comment: Accepted in the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Scienc

IT Competence in Internet Founder Teams - An Analysis of Preferences and Product Innovativity

In the Net Economy, numerous start-ups relying on Internet-based business models have been founded in the recent years. In these ventures IT experts are confronted with different requirements to those of traditional software development. It can thus be assumed that founders in the Net Economy prefer IT experts with a different competence profile. Based on an elaborate competence model for IT experts in Internet-based ventures, founder preferences are empirically analyzed and related to the novelty of the venture’s product. An adaptive conjoint analysis is applied to obtain utility values for single components of competence. Using cluster analysis, four different competence profiles are identified which correspond to prototypical IT experts bearing different core functions. Data analysis suggests that founders with more innovative products differ from founders with less innovative products in their perception of the optimal IT expert’s competence profile. The results have implications both for career decisions of IT experts and for founders of Internet start-ups who are looking for co-founding IT experts. This study is one of the first to explicitly focus on IT competence in Internet-based ventures. It therefore extends existing research on IT competence to a new and dynamic industry

Real-Time On-Board Obstacle Avoidance for UAVs based on Embedded Stereo Vision

In order to improve usability and safety, modern unmanned aerial vehicles (UAVs) are equipped with sensors to monitor the environment, such as laser-scanners and cameras. One important aspect in this monitoring process is to detect obstacles in the flight path in order to avoid collisions. Since a large number of consumer UAVs suffer from tight weight and power constraints, our work focuses on obstacle avoidance based on a lightweight stereo camera setup. We use disparity maps, which are computed from the camera images, to locate obstacles and to automatically steer the UAV around them. For disparity map computation we optimize the well-known semi-global matching (SGM) approach for the deployment on an embedded FPGA. The disparity maps are then converted into simpler representations, the so called U-/V-Maps, which are used for obstacle detection. Obstacle avoidance is based on a reactive approach which finds the shortest path around the obstacles as soon as they have a critical distance to the UAV. One of the fundamental goals of our work was the reduction of development costs by closing the gap between application development and hardware optimization. Hence, we aimed at using high-level synthesis (HLS) for porting our algorithms, which are written in C/C++, to the embedded FPGA. We evaluated our implementation of the disparity estimation on the KITTI Stereo 2015 benchmark. The integrity of the overall real-time reactive obstacle avoidance algorithm has been evaluated by using Hardware-in-the-Loop testing in conjunction with two flight simulators

Interdisciplinary Development and Evaluation of Cognitive Architectures Exemplified with the SiMA Approach

Abstract In this paper we show how simple simulation scenarios can be used to develop and test foundational functionalities of cognitive architectures, exemplified with the SiMA architecture. We present an interdisciplinary methodology that considers the challenges in capturing and evaluating basic functionalities of the human mind. In this regard, we structure and concretize assumptions from various disciplines and show how we evaluate their plausibility in a consistent model, using parametrized simulations

Mononuclear cell secretome protects from experimental autoimmune myocarditis

Aims Supernatants of serum-free cultured mononuclear cells (MNC) contain a mix of immunomodulating factors (secretome), which have been shown to attenuate detrimental inflammatory responses following myocardial ischaemia. Inflammatory dilated cardiomyopathy (iDCM) is a common cause of heart failure in young patients. Experimental autoimmune myocarditis (EAM) is a CD4+ T cell-dependent model, which mirrors important pathogenic aspects of iDCM. The aim of this study was to determine the influence of MNC secretome on myocardial inflammation in the EAM model. Methods and results BALB/c mice were immunized twice with an alpha myosin heavy chain peptide together with Complete Freund adjuvant. Supernatants from mouse mononuclear cells were collected, dialysed, and injected i.p. at Day 0, Day 7, or Day 14, respectively. Myocarditis severity, T cell responses, and autoantibody formation were assessed at Day 21. The impact of MNC secretome on CD4+ T cell function and viability was evaluated using in vitro proliferation and cell viability assays. A single high-dose application of MNC secretome, injected at Day 14 after the first immunization, effectively attenuated myocardial inflammation. Mechanistically, MNC secretome induced caspase-8-dependent apoptosis in autoreactive CD4+ T cells. Conclusion MNC secretome abrogated myocardial inflammation in a CD4+ T cell-dependent animal model of autoimmune myocarditis. This anti-inflammatory effect of MNC secretome suggests a novel and simple potential treatment concept for inflammatory heart disease

Professional Standards in Medical Ultrasound - EFSUMB Position Paper (Long Version) - General Aspects

This first position paper of the European Federation of Societies for Ultrasound in Medicine and Biology (EFSUMB) on professional standards presents a common position across the different medical professions within EFSUMB regarding optimal standards for the performing and reporting of ultrasound examinations by any professional ultrasound operator. It describes general aspects of professionality that ensure procedure quality, effectiveness, efficiency, and sustainability in virtually all application fields of medical ultrasound. Recommendations are given related to safety and indication of ultrasound examinations, requirements for examination rooms, structured examination, systematic reporting of results, and management, communication and archiving of ultrasound data. The print version of this article is a short version. The long version is published online.publishersversionPeer reviewe

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Cross-channel cooperation: a collaborative approach of integrating online and offline business models

Abstract: Due to the increasing use of e-business technologies, the corresponding Net Economy has evolved into an established trade level. It is characterized by numerous entrepreneurial ventures equipped with innovative online business models. Technological advance and changes in customer behaviour implicate that the physical and the electronic trade level are increasingly used complementarily. In order to be successful on both trade levels, traditional firms and Internet-based ventures inevitably need to approach each other. In this paper, we argue that collaborative concepts represent a promising way of meeting the resulting requirements. Crosschannel cooperation enables firms to integrate online and offline business models without extending themselves beyond their own means or competencies. Building upon market- and resource-based considerations, we argue why and how cross-channel cooperation contributes to competitive advantage and propose a classification of the resulting forms of collaboration.