Design and Control of the Mobile Micro Robot Alice

This paper describes the design methodology to build an autonomous mobile robot of just few cubic centimeters (2 x 2 x 2 cm). Starting from the expected features, the design path will be shown, going through solution proposition, component search, subsystems interconnections, several versions and ending to the final product. The second part of the paper will be dedicated to the control of such a robot which has implications in the control and software architecture. The overall design cycle results in the last version “Alice 2002” which has up to 10 hours autonomy with rechargeable battery, proximity sensors and remote control possibility. Furthermore many additional hardware modules like a radio or a linear camera can extend the basic capabilities. At the moment about 300 Alices exist and are used in various exhibitions and research programs

SCIM: Simultaneous Clustering, Inference, and Mapping for Open-World Semantic Scene Understanding

In order to operate in human environments, a robot's semantic perception has to overcome open-world challenges such as novel objects and domain gaps. Autonomous deployment to such environments therefore requires robots to update their knowledge and learn without supervision. We investigate how a robot can autonomously discover novel semantic classes and improve accuracy on known classes when exploring an unknown environment. To this end, we develop a general framework for mapping and clustering that we then use to generate a self-supervised learning signal to update a semantic segmentation model. In particular, we show how clustering parameters can be optimized during deployment and that fusion of multiple observation modalities improves novel object discovery compared to prior work. Models, data, and implementations can be found at https://github.com/hermannsblum/scimComment: accepted at ISRR 202

Multiresolution mapping and informative path planning for UAV-based terrain monitoring

© 2017 IEEE. Unmanned aerial vehicles (UAVs) can offer timely and cost-effective delivery of high-quality sensing data. However, deciding when and where to take measurements in complex environments remains an open challenge. To address this issue, we introduce a new multiresolution mapping approach for informative path planning in terrain monitoring using UAVs. Our strategy exploits the spatial correlation encoded in a Gaussian Process model as a prior for Bayesian data fusion with probabilistic sensors. This allows us to incorporate altitude-dependent sensor models for aerial imaging and perform constant-time measurement updates. The resulting maps are used to plan information-rich trajectories in continuous 3-D space through a combination of grid search and evolutionary optimization. We evaluate our framework on the application of agricultural biomass monitoring. Extensive simulations show that our planner performs better than existing methods, with mean error reductions of up to 45% compared to traditional 'lawnmower' coverage. We demonstrate proof of concept using a multirotor to map color in different environments

Transcriptomic characterization of two major Fusarium resistance quantitative trait loci (QTLs), Fhb1 and Qfhs.ifa-5A, identifies novel candidate genes

Fusarium head blight, caused by Fusarium graminearum, is a devastating disease of wheat. We developed near-isogenic lines (NILs) differing in the two strongest known F. graminearum resistance quantitative trait loci (QTLs), Qfhs.ndsu-3BS (also known as resistance gene Fhb1) and Qfhs.ifa-5A, which are located on the short arm of chromosome 3B and on chromosome 5A, respectively. These NILs showing different levels of resistance were used to identify transcripts that are changed significantly in a QTL-specific manner in response to the pathogen and between mock-inoculated samples. After inoculation with F. graminearum spores, 16 transcripts showed a significantly different response for Fhb1 and 352 for Qfhs.ifa-5A. Notably, we identified a lipid transfer protein which is constitutively at least 50-fold more abundant in plants carrying the resistant allele of Qfhs.ifa-5A. In addition to this candidate gene associated with Qfhs.ifa-5A, we identified a uridine diphosphate (UDP)-glycosyltransferase gene, designated TaUGT12887, exhibiting a positive difference in response to the pathogen in lines harbouring both QTLs relative to lines carrying only the Qfhs.ifa-5A resistance allele, suggesting Fhb1 dependence of this transcript. Yet, this dependence was observed only in the NIL with already higher basal resistance. The complete cDNA of TaUGT12887 was reconstituted from available wheat genomic sequences, and a synthetic recoded gene was expressed in a toxin-sensitive strain of Saccharomyces cerevisiae. This gene conferred deoxynivalenol resistance, albeit much weaker than that observed with the previously characterized barley HvUGT13248

An integrated cryogenic optical modulator

Integrated electrical and photonic circuits (PIC) operating at cryogenic temperatures are fundamental building blocks required to achieve scalable quantum computing, and cryogenic computing technologies. Optical interconnects offer better performance and thermal insulation than electrical wires and are imperative for true quantum communication. Silicon PICs have matured for room temperature applications but their cryogenic performance is limited by the absence of efficient low temperature electro-optic (EO) modulation. While detectors and lasers perform better at low temperature, cryogenic optical switching remains an unsolved challenge. Here we demonstrate EO switching and modulation from room temperature down to 4 K by using the Pockels effect in integrated barium titanate (BaTiO3)-based devices. We report the nonlinear optical (NLO) properties of BaTiO3 in a temperature range which has previously not been explored, showing an effective Pockels coefficient of 200 pm/V at 4 K. We demonstrate the largest EO bandwidth (30 GHz) of any cryogenic switch to date, ultra-low-power tuning which is 10^9 times more efficient than thermal tuning, and high-speed data modulation at 20 Gbps. Our results demonstrate a missing component for cryogenic PICs. It removes major roadblocks for the realisation of novel cryogenic-compatible systems in the field of quantum computing and supercomputing, and for interfacing those systems with the real world at room-temperature

Conceptual spatial representations for indoor mobile robots

We present an approach for creating conceptual representations of human-made indoor environments using mobile robots. The concepts refer to spatial and functional properties of typical indoor environments. Following findings in cognitive psychology, our model is composed of layers representing maps at different levels of abstraction. The complete system is integrated in a mobile robot endowed with laser and vision sensors for place and object recognition. The system also incorporates a linguistic framework that actively supports the map acquisition process, and which is used for situated dialogue. Finally, we discuss the capabilities of the integrated system

Probabilistic Plane Fitting in 3D and an Application to Robotic Mapping

This paper presents a method for probabilistic plane fitting and an application to robotic 3D mapping. The plane is fitted in an orthogonal least-square sense and the output complies with the conventions of the Symmetries and Perturbation model (SPmodel). In the second part of the paper, the presented plane fitting method is used within a 3D mapping application. It is shown that by using probabilistic information, high precision 3D maps can be generate