Integrierte Multi-Sensor-Fusion für die simultane Lokalisierung und Kartenerstellung für mobile Robotersysteme

In this work, probabilistic methods for combining multiple sensors utilizing multi-sensor fusion for robust and precise localization and mapping in heterogeneous outdoor environments are presented. Aspects of increasing the reliability of landmark recognition are highlighted, as well as the integration of additional absolute and relative sensors using advanced filtering techniques

Efficient Global Occupancy Mapping for Mobile Robots using OpenVDB

In this work we present a fast occupancy map building approach based on the VDB datastructure. Existing log-odds based occupancy mapping systems are often not able to keep up with the high point densities and framerates of modern sensors. Therefore, we suggest a highly optimized approach based on a modern datastructure coming from a computer graphic background. A multithreaded insertion scheme allows occupancy map building at unprecedented speed. Multiple optimizations allow for a customizable tradeoff between runtime and map quality. We first demonstrate the effectiveness of the approach quantitatively on a set of ablation studies and typical benchmark sets, before we practically demonstrate the system using a legged robot and a UAV.Comment: 6 pages, presented in Agile Robotics Workshop at IROS202

Western Diet-Fed, Aortic-Banded Ossabaw Swine: A Preclinical Model of Cardio-Metabolic Heart Failure.

The development of new treatments for heart failure lack animal models that encompass the increasingly heterogeneous disease profile of this patient population. This report provides evidence supporting the hypothesis that Western Diet-fed, aortic-banded Ossabaw swine display an integrated physiological, morphological, and genetic phenotype evocative of cardio-metabolic heart failure. This new preclinical animal model displays a distinctive constellation of findings that are conceivably useful to extending the understanding of how pre-existing cardio-metabolic syndrome can contribute to developing HF

T-cell recognition of chemicals, protein allergens and drugs: towards the development of in vitro assays

Chemicals can elicit T-cell-mediated diseases such as allergic contact dermatitis and adverse drug reactions. Therefore, testing of chemicals, drugs and protein allergens for hazard identification and risk assessment is essential in regulatory toxicology. The seventh amendment of the EU Cosmetics Directive now prohibits the testing of cosmetic ingredients in mice, guinea pigs and other animal species to assess their sensitizing potential. In addition, the EU Chemicals Directive REACh requires the retesting of more than 30,000 chemicals for different toxicological endpoints, including sensitization, requiring vast numbers of animals. Therefore, alternative methods are urgently needed to eventually replace animal testing. Here, we summarize the outcome of an expert meeting in Rome on 7 November 2009 on the development of T-cell-based in vitro assays as tools in immunotoxicology to identify hazardous chemicals and drugs. In addition, we provide an overview of the development of the field over the last two decades

3D SLAM with scan matching and factor graph optimization

For autonomous navigation, a mobile robot needs the capability to estimate its pose while simultaneously mapping its environment. This contribution presents an approach for fusing data from multiple asynchronous sensors using factor graphs. Full 3D SLAM is performed on data from several localization sensors and point clouds from a 3D LiDAR. The scans from the LiDAR are integrated by scan matching for relative motion estimation and are also used for loop closure

Safe mobile robot motion planning for waypoint sequences in a dynamic environment

Safe and efficient path planning for mobile robots in dynamic environments is still a challenging research topic. Most approaches use separate algorithms for global path planning and local obstacle avoidance. Furthermore, planning a path for a sequence of goals is mostly done by planning to each next goal individually. These two strategies generally result in sub-optimal navigation strategies. In this paper, we present an algorithm which addresses these problems in a single combined approach. For this purpose, we model the static and dynamic risk of the environment in a consistent way and propose a novel graph structure based on a state x time x goal lattice with hybrid dimensionality. It allows the joint planning for multiple goals while incorporating collision risk due to dynamic and static obstacles. It computes hybrid solutions which are part trajectory and part path. Finally, we provide some results of our algorithm in action to prove its high quality solutions and real-time capability

Performance Optimization of Autonomous Platforms inUnstructured Outdoor Environments Using a Novel Constrained Planning Approach

We propose a novel constrained planning approach for autonomous vehicles in unstructured outdoor environments. Our method enables autonomous off-road platforms to keep a predetermined track accurately, but in the same time allows the avoidance of static obstacles and dynamic objects. Two application scenarios are presented according to common transport behaviors with obstacle avoidance: Mule and Convoying. Our method is real-time integrated in a typical processing pipeline for autonomous driving in unstructured outdoor environments. It provides a constrained planning area, subsequently designated cost valley. Our cost valley keeps the trajectory of the vehicle both smooth in difficult passages and close to the desired track. The efficiency of our method is demonstrated on two autonomous platforms with a huge difference in kinematics, weight and size - a small electric platform and an off-road truck. It directly improves the behavior of autonomous vehicles, especially in critical passages

Toward a multifaceted platform for humanitarian demining: Paper presented at 13th IARP Workshop on Humanitarian Demining and Risky Interventions, HUDEM 2015, Beograd, Croatia, 27-28 April 2015

The D-BOX project aims to increase deminers' confidence in technology developing a web-enabled platform which allows them to better utilize existing technologies and foster the development of the use of new ones. The idea behind D-BOX is to create an Information Management System which incorporates the process of Land Release, whereby the use of technologies is part of the process. The system will be flexible to adapt to local needs but at the same time it will be compliant with the IMAS. In a complex domain like demining, single technologies are rarely effective. The new platform will foster functional tool chains to realize complex tasks, information merging and synergies amongst heterogeneous tools to increase the effectiveness of the tool combinations. In the paper we establish the requirements for the new platform and give examples of Functional Tool Chain(s) and of Synergies among tools being developed by D-BOX partners