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To realize the immense potential of large-scale genomic sequencing after the completion of the second human genome (Venter's), the costs for the complete sequencing of additional genomes must be dramatically reduced. Among the technologies being developed to reduce sequencing costs, microchip electrophoresis is the only new technology ready to produce the long reads most suitable for the de novo sequencing and assembly of large and complex genomes. Compared with the current paradigm of capillary electrophoresis, microchip systems promise to reduce sequencing costs dramatically by increasing throughput, reducing reagent consumption, and integrating the many steps of the sequencing pipeline onto a single platform. Although capillary-based systems require [almost equal to]70 min to deliver [almost equal to]650 bases of contiguous sequence, we report sequencing up to 600 bases in just 6.5 min by microchip electrophoresis with a unique polymer matrix/adsorbed polymer wall coating combination. This represents a two-thirds reduction in sequencing time over any previously published chip sequencing result, with comparable read length and sequence quality. We hypothesize that these ultrafast long reads on chips can be achieved because the combined polymer system engenders a recently discovered \"hybrid\" mechanism of DNA electromigration, in which DNA molecules alternate rapidly between reptating through the intact polymer network and disrupting network entanglements to drag polymers through the solution, similar to dsDNA dynamics we observe in single-molecule DNA imaging studies. Most importantly, these results reveal the surprisingly powerful ability of microchip electrophoresis to provide ultrafast Sanger sequencing, which will translate to increased system throughput and reduced costs.

We present a multirotor Unmanned Aerial Vehicle (UAV) control and estimation system for supporting replicable research through realistic simulations and real-world experiments. We propose a unique multi-frame localization paradigm for estimating the states of a UAV in various frames of reference using multiple sensors simultaneously. The system enables complex missions in GNSS and GNSS-denied environments, including outdoor-indoor transitions and the execution of redundant estimators for backing up unreliable localization sources. Two feedback control designs are presented: one for precise and aggressive maneuvers, and the other for stable and smooth flight with a noisy state estimate. The proposed control and estimation pipeline are constructed without using the Euler/Tait-Bryan angle representation of orientation in 3D. Instead, we rely on rotation matrices and a novel heading-based convention to represent the one free rotational degree-of-freedom in 3D of a standard multirotor helicopter. We provide an actively maintained and well-documented open-source implementation, including realistic simulation of UAV, sensors, and localization systems. The proposed system is the product of years of applied research on multi-robot systems, aerial swarms, aerial manipulation, motion planning, and remote sensing. All our results have been supported by real-world system deployment that subsequently shaped the system into the form presented here. In addition, the system was utilized during the participation of our team from the Czech Technical University in Prague in the prestigious MBZIRC 2017 and 2020 robotics competitions, and also in the DARPA Subterranean challenge. Each time, our team was able to secure top places among the best competitors from all over the world.

In this paper, we introduce a distributed autonomous flocking behavior of Unmanned Aerial Vehicles (UAVs) in demanding outdoor conditions, motivated by search and rescue applications. We propose a novel approach for decentralized swarm navigation in the direction of a candidate object of interest (OOI) based on real-time detections from onboard RGB cameras. A novel self-adaptive communication strategy secures an efficient change of swarm azimuth to a higher priority direction based on the real-time detections. We introduce a local visual communication channel that establishes a network connection between neighboring robots without explicit communication to achieve high reliability and scalability of the system. As a case study, this novel method is applied for the deployment of a UAV swarm towards detected OOI for closer inspection and verification. The results of simulations and real-world experiments have verified the intended behavior of the swarm system for the detection of true positive and false positive OOI, as well as for cooperative environment exploration.

This paper presents a novel approach for control and motion planning of formations of multiple unmanned micro aerial vehicles (multi-rotor helicopters, in the literature also often called unmanned aerial vehicles—UAVs or unmanned aerial system—UAS) in cluttered GPS-denied on straitened environments. The proposed method enables us to autonomously design complex maneuvers of a compact Micro Aerial Vehicles (MAV) team in a virtual-leader-follower scheme. The results of the motion planning approach and the required stability of the formation are achieved by migrating the virtual leader along with the hull surrounding the formation. This enables us to suddenly change the formation motion in all directions, independently from the current orientation of the formation, and therefore to fully exploit the maneuverability of small multi-rotor helicopters. The proposed method was verified and its performance has been statistically evaluated in numerous simulations and experiments with a fleet of MAVs.

This paper presents a modular autonomous Unmanned Aerial Vehicle (UAV) platform called the Multi-robot System (MRS) Drone that can be used in a large range of indoor and outdoor applications. The MRS Drone features unique modularity changes in actuators, frames, and sensory configuration. As the name suggests, the platform is specially tailored for deployment within a MRS group. The MRS Drone contributes to the state-of-the-art of UAV platforms by allowing smooth real-world deployment of multiple aerial robots, as well as by outperforming other platforms with its modularity. For real-world multi-robot deployment in various applications, the platform is easy to both assemble and modify. Moreover, it is accompanied by a realistic simulator to enable safe pre-flight testing and a smooth transition to complex real-world experiments. In this manuscript, we present mechanical and electrical designs, software architecture, and technical specifications to build a fully autonomous multi UAV system. Finally, we demonstrate the full capabilities and the unique modularity of the MRS Drone in various real-world applications that required a diverse range of platform configurations.

We present a multirotor Unmanned Aerial Vehicle control (UAV) and estimation system for supporting replicable research through realistic simulations and real-world experiments. We propose a unique multi-frame localization paradigm for estimating the states of a UAV in various frames of reference using multiple sensors simultaneously. The system enables complex missions in GNSS and GNSS-denied environments, including outdoor-indoor transitions and the execution of redundant estimators for backing up unreliable localization sources. Two feedback control designs are presented: one for precise and aggressive maneuvers, and the other for stable and smooth flight with a noisy state estimate. The proposed control and estimation pipeline are constructed without using the Euler/Tait-Bryan angle representation of orientation in 3D. Instead, we rely on rotation matrices and a novel heading-based convention to represent the one free rotational degree-of-freedom in 3D of a standard multirotor helicopter. We provide an actively maintained and well-documented open-source implementation, including realistic simulation of UAV, sensors, and localization systems. The proposed system is the product of years of applied research on multi-robot systems, aerial swarms, aerial manipulation, motion planning, and remote sensing. All our results have been supported by real-world system deployment that shaped the system into the form presented here. In addition, the system was utilized during the participation of our team from the CTU in Prague in the prestigious MBZIRC 2017 and 2020 robotics competitions, and also in the DARPA SubT challenge. Each time, our team was able to secure top places among the best competitors from all over the world. On each occasion, the challenges has motivated the team to improve the system and to gain a great amount of high-quality experience within tight deadlines.

This paper presents a novel approach for autonomous cooperating UAVs in search and rescue operations in subterranean domains with complex topology. The proposed system was ranked second in the Virtual Track of the DARPA SubT Finals as part of the team CTU-CRAS-NORLAB. In contrast to the winning solution that was developed specifically for the Virtual Track, the proposed solution also proved to be a robust system for deployment onboard physical UAVs flying in the extremely harsh and confined environment of the real-world competition. The proposed approach enables fully autonomous and decentralized deployment of a UAV team with seamless simulation-to-world transfer, and proves its advantage over less mobile UGV teams in the flyable space of diverse environments. The main contributions of the paper are present in the mapping and navigation pipelines. The mapping approach employs novel map representations -- SphereMap for efficient risk-aware long-distance planning, FacetMap for surface coverage, and the compressed topological-volumetric LTVMap for allowing multi-robot cooperation under low-bandwidth communication. These representations are used in navigation together with novel methods for visibility-constrained informed search in a general 3D environment with no assumptions about the environment structure, while balancing deep exploration with sensor-coverage exploitation. The proposed solution also includes a visual-perception pipeline for on-board detection and localization of objects of interest in four RGB stream at 5 Hz each without a dedicated GPU. Apart from participation in the DARPA SubT, the performance of the UAV system is supported by extensive experimental verification in diverse environments with both qualitative and quantitative evaluation.

This paper presents a modular autonomous Unmanned Aerial Vehicle (UAV) platform called the Multi-robot Systems (MRS) Drone that can be used in a large range of indoor and outdoor applications. The MRS Drone features unique modularity with respect to changes in actuators, frames, and sensory configuration. As the name suggests, the platform is specially tailored for deployment within a MRS group. The MRS Drone contributes to the state-of-the-art of UAV platforms by allowing smooth real-world deployment of multiple aerial robots, as well as by outperforming other platforms with its modularity. For real-world multi-robot deployment in various applications, the platform is easy to both assemble and modify. Moreover, it is accompanied by a realistic simulator to enable safe pre-flight testing and a smooth transition to complex real-world experiments. In this manuscript, we present mechanical and electrical designs, software architecture, and technical specifications to build a fully autonomous multi UAV system. Finally, we demonstrate the full capabilities and the unique modularity of the MRS Drone in various real-world applications that required a diverse range of platform configurations.

Electrophoresis of DNA molecules through entangled polymer solutions continues to be an important tool for genetic analyses, including DNA sequencing and forensic genotyping. To date, many various polymer classes have been developed to perform such assays, but no completely predictive mechanistic understanding of these electrophoretic separations in microfluidic channels exists. Previous DNA sequencing studies have reported sequencing read lengths in polymer matrices, using specific polymer molar masses or concentrations for individual cases. Other work has focused on developing predictive models for DNA separation in entangled polymers in capillary-based systems. The aim of this research is to develop polymer systems for high performance separations of single stranded DNA in glass microfluidic chips. Engineered polymer systems are described in which the physical and the chemical nature of the polymer matrix are manipulated to provide higher quality separations. Binary blends of poly(N,N-dimethylacrylamide) (pDMA) are studied in order to maintain high sequencing read lengths while reducing the overall viscosity of the polymer matrix, thereby increasing its ease of use. A library of poly(acrylamide-co-dimethylacrylamide) copolymers was synthesized to characterize the effect of polymer chemistry on the separation of DNA fragments. Through comprehensive analysis of the electrophoretic migration of ssDNA in each matrix, optimal conditions were identified under which each copolymer should be used to provide the best separation in that matrix. Finally, thorough examination of the physical properties of a very high molar mass pDMA proved that loading the polymer under high stress causes high degrees of deformation within the polymer matrix. For sufficiently large polymers used for DNA separations, these stresses cannot be dissipated quickly by chain dynamics and there is a high degree of chain relaxation occurring while electrophoresis is being performed, leading to lower resolution separations. These effects can be minimized simply by understanding the dynamic properties of the polymer separation matrix and working within a set of parameters to yield high quality DNA separations.

This paper presents a family of autonomous Unmanned Aerial Vehicles (UAVs) platforms designed for a diverse range of indoor and outdoor applications. The proposed UAV design is highly modular in terms of used actuators, sensor configurations, and even UAV frames. This allows to achieve, with minimal effort, a proper experimental setup for single, as well as, multi robot scenarios. Presented platforms are intended to facilitate the transition from simulations, and simplified laboratory experiments, into the deployment of aerial robots into uncertain and hard-to-model real-world conditions. We present mechanical designs, electric configurations, and dynamic models of the UAVs, followed by numerous recommendations and technical details required for building such a fully autonomous UAV system for experimental verification of scientific achievements. To show strength and high variability of the proposed system, we present results of tens of completely different real-robot experiments in various environments using distinct actuator and sensory configurations.