CA : A Cancer Journal for Clinicians

International Joint Conference on Neural Networks

Technologies such as batteries, biomaterials and heterogeneous catalysts have functions that are defined by mixtures of molecular and mesoscale components. As yet, this multi-length-scale complexity cannot be fully captured by atomistic simulations, and the design of such materials from first principles is still rare1–5. Likewise, experimental complexity scales exponentially with the number of variables, restricting most searches to narrow areas of materials space. Robots can assist in experimental searches6–14 but their widespread adoption in materials research is challenging because of the diversity of sample types, operations, instruments and measurements required. Here we use a mobile robot to search for improved photocatalysts for hydrogen production from water15. The robot operated autonomously over eight days, performing 688 experiments within a ten-variable experimental space, driven by a batched Bayesian search algorithm16–18. This autonomous search identified photocatalyst mixtures that were six times more active than the initial formulations, selecting beneficial components and deselecting negative ones. Our strategy uses a dexterous19,20 free-roaming robot21–24, automating the researcher rather than the instruments. This modular approach could be deployed in conventional laboratories for a range of research problems beyond photocatalysis. A mobile robot autonomously operates analytical instruments in a wet chemistry laboratory, performing a photocatalyst optimization task much faster than a human would be able to.

/pdf/a-mobile-robotic-chemist-204cvrj0qk.pdf

A mobile robotic chemist

Learning and then recognizing a route, whether travelled during the day or at night, in clear or inclement weather, and in summer or winter is a challenging task for state of the art algorithms in computer vision and robotics. In this paper, we present a new approach to visual navigation under changing conditions dubbed SeqSLAM. Instead of calculating the single location most likely given a current image, our approach calculates the best candidate matching location within every local navigation sequence. Localization is then achieved by recognizing coherent sequences of these “local best matches”. This approach removes the need for global matching performance by the vision front-end - instead it must only pick the best match within any short sequence of images. The approach is applicable over environment changes that render traditional feature-based techniques ineffective. Using two car-mounted camera datasets we demonstrate the effectiveness of the algorithm and compare it to one of the most successful feature-based SLAM algorithms, FAB-MAP. The perceptual change in the datasets is extreme; repeated traverses through environments during the day and then in the middle of the night, at times separated by months or years and in opposite seasons, and in clear weather and extremely heavy rain. While the feature-based method fails, the sequence-based algorithm is able to match trajectory segments at 100% precision with recall rates of up to 60%.

SeqSLAM : visual route-based navigation for sunny summer days and stormy winter nights

IEEE International Joint Conference on Neural Networks

Indoor Positioning Systems of Mobile Robots: A Review

The paper presents a control system for mobile robots in distributed life science laboratories. The system covers all technical aspects of laboratory mobile robotics. In this system: (a) to get an accurate and low-cost robot localization, a method using a StarGazer module with a number of ceiling landmarks is utilized; (b) to have an expansible communication network, a standard IEEE 802.11g wireless network is adopted and a XML-based command protocol is designed for the communication between the remote side and the robot board side; (c) to realize a function of dynamic obstacle measurement and collision avoidance, an artificial potential field method based on a Microsoft Kinect sensor is used; and (d) to determine the shortest paths for transportation tasks, a hybrid planning strategy based on a Floyd algorithm and a Genetic Algorithm (GA) is proposed. Additionally, to make the traditional GA method suitable for the laboratory robot's routing, a series of optimized works are also provided in detail. Two experiments show that the proposed system and its control strategy are effective for a complex life science laboratory.

https://journals.sagepub.com/doi/pdf/10.5772/56670

Mobile Robot for Life Science Automation

A common wireless remote control system based on standard APIs of robots is presented to enable a stable multi-robot transportation in distributed life science laboratories. This system consists of multi-robot board control centers (PCs), a remote server control center (PC), a wireless communication network and an infrared radio navigation module with ceiling passive landmarks. To let this system expand conveniently, the two-level Client/Server architecture is adopted, and a standard IEEE 802.11g wireless communication with TCP/IP protocol is utilized. An inside architecture is employed for signal sampling and controlling between robot board PCs and the robot's hardware modules. An additional outside architecture is designed for higher remote commands between robot board PCs and remote server control PC. Two experiments in this study show that the simple ceiling landmark method is suitable for the robot indoor navigation with low costs, and this kind of remote control system can work effectively in large and distributed laboratory.

A common wireless remote control system for mobile robots in laboratory

Automated cell cultivation is an important tool for simplifying routine laboratory work. Automated methods are independent of skill levels and daily constitution of laboratory staff in combination with a constant quality and performance of the methods. The Biomek Cell Workstation was configured as a flexible and compatible system. The modified Biomek Cell Workstation enables the cultivation of adherent and suspension cells. Until now, no commercially available systems enabled the automated handling of both types of cells in one system. In particular, the automated cultivation of suspension cells in this form has not been published. The cell counts and viabilities were nonsignificantly decreased for cells cultivated in AutoFlasks in automated handling. The proliferation of manual and automated bioscreening by the WST-1 assay showed a nonsignificant lower proliferation of automatically disseminated cells associated with a mostly lower standard error. The disseminated suspension cell lines showed different pronounced proliferations in descending order, starting with Jurkat cells followed by SEM, Molt4, and RS4 cells having the lowest proliferation. In this respect, we successfully disseminated and screened suspension cells in an automated way. The automated cultivation and dissemination of a variety of suspension cells can replace the manual method.

https://journals.sagepub.com/doi/pdf/10.1177/2211068215599786

Biomek Cell Workstation: A Variable System for Automated Cell Cultivation.

In recent years the degree of automation in life science laboratories increased considerably by introducing stationary and mobile robots. This trend requires intensified considerations of the occupational safety for cooperating humans, since the robots operate with low volatile compounds that partially emit hazardous vapors, which especially do arise if accidents or leakages occur. For the fast detection of such or similar situations a modular IoT-sensor node was developed. The sensor node consists of four hardware layers, which can be configured individually regarding basic functionality and measured parameters for varying application focuses. In this paper the sensor node is equipped with two gas sensors (BME688, SGP30) for a continuous TVOC measurement. In investigations under controlled laboratory conditions the general sensors’ behavior regarding different VOCs and varying installation conditions are performed. In practical investigations the sensor node’s integration into simple laboratory applications using stationary and mobile robots is shown and examined. The investigation results show that the selected sensors are suitable for the early detection of solvent vapors in life science laboratories. The sensor response and thus the system’s applicability depends on the used compounds, the distance between sensor node and vapor source as well as the speed of the automation systems.

Flexible IoT Gas Sensor Node for Automated Life Science Environments Using Stationary and Mobile Robots.

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