Observer-based Controller for VTOL-UAVs Tracking using Direct Vision-Aided Inertial Navigation Measurements

This paper proposes a novel observer-based controller for Vertical Take-Off and Landing (VTOL) Unmanned Aerial Vehicle (UAV) designed to directly receive measurements from a Vision-Aided Inertial Navigation System (VA-INS) and produce the required thrust and rotational torque inputs. The VA-INS is composed of a vision unit (monocular or stereo camera) and a typical low-cost 6-axis Inertial Measurement Unit (IMU) equipped with an accelerometer and a gyroscope. A major benefit of this approach is its applicability for environments where the Global Positioning System (GPS) is inaccessible. The proposed VTOL-UAV observer utilizes IMU and feature measurements to accurately estimate attitude (orientation), gyroscope bias, position, and linear velocity. Ability to use VA-INS measurements directly makes the proposed observer design more computationally efficient as it obviates the need for attitude and position reconstruction. Once the motion components are estimated, the observer-based controller is used to control the VTOL-UAV attitude, angular velocity, position, and linear velocity guiding the vehicle along the desired trajectory in six degrees of freedom (6 DoF). The closed-loop estimation and the control errors of the observer-based controller are proven to be exponentially stable starting from almost any initial condition. To achieve global and unique VTOL-UAV representation in 6 DoF, the proposed approach is posed on the Lie Group and the design in unit-quaternion is presented. Although the proposed approach is described in a continuous form, the discrete version is provided and tested. Keywords: Vision-aided inertial navigation system, unmanned aerial vehicle, vertical take-off and landing, stochastic, noise, Robotics, control systems, air mobility, observer-based controller algorithm, landmark measurement, exponential stability

Recovering the state sequence of hidden Markov models using mean-field approximations

Inferring the sequence of states from observations is one of the most fundamental problems in Hidden Markov Models. In statistical physics language, this problem is equivalent to computing the marginals of a one-dimensional model with a random external field. While this task can be accomplished through transfer matrix methods, it becomes quickly intractable when the underlying state space is large. This paper develops several low-complexity approximate algorithms to address this inference problem when the state space becomes large. The new algorithms are based on various mean-field approximations of the transfer matrix. Their performances are studied in detail on a simple realistic model for DNA pyrosequencing.Comment: 43 pages, 41 figure

Degradable Terpolymers with Alkyl Side Chains Demonstrate Enhanced Gene Delivery Potency and Nanoparticle Stability

Degradable, cationic poly(β-amino ester)s (PBAEs) with alkyl side chains are developed for non-viral gene delivery. Nanoparticles formed from these PBAE terpolymers exhibit significantly enhanced DNA transfection potency and resistance to aggregation. These hydrophobic PBAE terpolymers, but not PBAEs lacking alkyl side chains, support interaction with PEG-lipid conjugates, facilitating their functionalization with shielding and targeting moieties and accelerating the in vivo translation of these materials.National Heart, Lung, and Blood InstituteNational Institutes of Health (U.S.) (Program of Excellence in Nanotechnology (PEN) Award, Contract #HHSN268201000045C)National Institutes of Health (U.S.) (NIH Grant R01-EB000244-27)National Institutes of Health (U.S.) (NIH Grant 5-R01-CA132091-04)National Institutes of Health (U.S.) (NIH Grant R01-DE016516-03)National Science Foundation (U.S.) (Graduate Research Fellowship)Juvenile Diabetes Research Foundation International (Grant 17–2007-1063

Nonlinear Deterministic Observer for Inertial Navigation using Ultra-wideband and IMU Sensor Fusion

Navigation in Global Positioning Systems (GPS)-denied environments requires robust estimators reliant on fusion of inertial sensors able to estimate rigid-body's orientation, position, and linear velocity. Ultra-wideband (UWB) and Inertial Measurement Unit (IMU) represent low-cost measurement technology that can be utilized for successful Inertial Navigation. This paper presents a nonlinear deterministic navigation observer in a continuous form that directly employs UWB and IMU measurements. The estimator is developed on the extended Special Euclidean Group $\mathbb{SE}_{2}\left(3\right)$ and ensures exponential convergence of the closed loop error signals starting from almost any initial condition. The discrete version of the proposed observer is tested using a publicly available real-world dataset of a drone flight. Keywords: Ultra-wideband, Inertial measurement unit, Sensor Fusion, Positioning system, GPS-denied navigation.Comment: 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS

Effect of molecular weight of amine end-modified poly(β-amino ester)s on gene delivery efficiency and toxicity

Amine end-modified poly(β-amino ester)s (PBAEs) have generated interest as efficient, biodegradable polymeric carriers for plasmid DNA (pDNA). For cationic, non-degradable polymers, such as polyethylenimine (PEI), the polymer molecular weight (MW) and molecular weight distribution (MWD) significantly affect transfection activity and cytotoxicity. The effect of MW on DNA transfection activity for PBAEs has been less well studied. We applied two strategies to obtain amine end-modified PBAEs varying in MW. In one approach, we synthesized four amine end-modified PBAEs with each at 15 different monomer molar ratios, and observed that polymers of intermediate length mediated optimal DNA transfection in HeLa cells. Biophysical characterization of these feed ratio variants suggested that optimal performance was related to higher DNA complexation efficiency and smaller nanoparticle size, but not to nanoparticle charge. In a second approach, we used preparative size exclusion chromatography (SEC) to obtain well-defined, monodisperse polymer fractions. We observed that the transfection activities of size-fractionated PBAEs generally increased with MW, a trend that was weakly associated with an increase in DNA binding efficiency. Furthermore, this approach allowed for the isolation of polymer fractions with greater transfection potency than the starting material. For researchers working with gene delivery polymers synthesized by step-growth polymerization, our data highlight the potentially broad utility of preparative SEC to isolate monodisperse polymers with improved properties. Overall, these results help to elucidate the influence of polymer MWD on nucleic acid delivery and provide insight toward the rational design of next-generation materials for gene therapy.Alnylam Pharmaceuticals (Firm)National Institutes of Health (U.S.) (Grant R01-EB000244-27)National Institutes of Health (U.S.) (Grant 5-R01-CA132091-04)National Science Foundation (U.S.). Graduate Research FellowshipNational Institutes of Health (U.S.). Ruth L. Kirschstein National Research Service Award (F32-EB011867

Nucleic acid-mediated intracellular protein delivery by lipid-like nanoparticles

Intracellular protein delivery has potential biotechnological and therapeutic application, but remains technically challenging. In contrast, a plethora of nucleic acid carriers have been developed, with lipid-based nanoparticles (LNPs) among the most clinically advanced reagents for oligonucleotide delivery. Here, we validate the hypothesis that oligonucleotides can serve as packaging materials to facilitate protein entrapment within and intracellular delivery by LNPs. Using two distinct model proteins, horseradish peroxidase and NeutrAvidin, we demonstrate that LNPs can yield efficient intracellular protein delivery in vitro when one or more oligonucleotides have been conjugated to the protein cargo. Moreover, in experiments with NeutrAvidin in vivo, we show that oligonucleotide conjugation significantly enhances LNP-mediated protein uptake within various spleen cell populations, suggesting that this approach may be particularly suitable for improved delivery of protein-based vaccines to antigen-presenting cells.National Heart, Lung, and Blood Institute (Contract HHSN268201000045C)National Institutes of Health (U.S.) (Grant R01-EB000244-27)National Institutes of Health (U.S.) (Grant 5-R01-CA132091-04)National Science Foundation (U.S.)Juvenile Diabetes Research Foundation International (Grant 17–2007-1063)United States. Dept. of Defense. Congressionally Directed Medical Research Programs (Grant W81XWH-13-1-0215

Alkane-modified short polyethyleneimine for siRNA delivery

RNA interference (RNAi) is a highly specific gene-silencing mechanism triggered by small interfering RNA (siRNA). Effective intracellular delivery requires the development of potent siRNA carriers. Here, we describe the synthesis and screening of a series of siRNA delivery materials. Short polyethyleneimine (PEI, Mw 600) was selected as a cationic backbone to which lipid tails were conjugated at various levels of saturation. In solution these polymer–lipid hybrids self-assemble to form nanoparticles capable of complexing siRNA. The complexes silence genes specifically and with low cytotoxicity. The efficiency of gene knockdown increased as the number of lipid tails conjugated to the PEI backbone increased. This is explained by reducing the binding affinity between the siRNA strands to the complex, thereby enabling siRNA release after cellular internalization. These results highlight the importance of complexation strength when designing siRNA delivery materials.Misrock FoundationAmerican Society for Engineering Education. National Defense Science and Engineering Graduate FellowshipNational Institutes of Health (U.S) (Grant EB000244)National Cancer Institute (U.S.) (MIT-Harvard Center of Cancer Nanotechnology Excellence. Grant CA151884)National Science Foundation (U.S.)Massachusetts Institute of Technology (Presidential Fellowships

Efficient thermal face recognition method using optimized curvelet features for biometric authentication

Biometric technology is becoming increasingly prevalent in several vital applications that substitute traditional password and token authentication mechanisms. Recognition accuracy and computational cost are two important aspects that are to be considered while designing biometric authentication systems. Thermal imaging is proven to capture a unique thermal signature for a person and thus has been used in thermal face recognition. However, the literature did not thoroughly analyse the impact of feature selection on the accuracy and computational cost of face recognition which is an important aspect for limited resources applications like IoT ones. Also, the literature did not thoroughly evaluate the performance metrics of the proposed methods/solutions which are needed for the optimal configuration of the biometric authentication systems. This paper proposes a thermal face-based biometric authentication system. The proposed system comprises five phases: a) capturing the user’s face with a thermal camera, b) segmenting the face region and excluding the background by optimized superpixel-based segmentation technique to extract the region of interest (ROI) of the face, c) feature extraction using wavelet and curvelet transform, d) feature selection by employing bio-inspired optimization algorithms: grey wolf optimizer (GWO), particle swarm optimization (PSO) and genetic algorithm (GA), e) the classification (user identification) performed using classifiers: random forest (RF), k-nearest neighbour (KNN), and naive bayes (NB). Upon the public dataset, Terravic Facial IR, the proposed system was evaluated using the metrics: accuracy, precision, recall, F-measure, and receiver operating characteristic (ROC) area. The results showed that the curvelet features optimized using the GWO and classified with random forest could help in authenticating users through thermal images with performance up to 99.5% which is better than the results of wavelet features by 10% while the former used 5% fewer features. In addition, the statistical analysis showed the significance of our proposed model. Compared to the related works, our system showed to be a better thermal face authentication model with a minimum set of features, making it computational-friendly

Lipidoid-Coated Iron Oxide Nanoparticles for Efficient DNA and siRNA delivery

The safe, targeted and effective delivery of gene therapeutics remains a significant barrier to their broad clinical application. Here we develop a magnetic nucleic acid delivery system composed of iron oxide nanoparticles and cationic lipid-like materials termed lipidoids. Coated nanoparticles are capable of delivering DNA and siRNA to cells in culture. The mean hydrodynamic size of these nanoparticles was systematically varied and optimized for delivery. While nanoparticles of different sizes showed similar siRNA delivery efficiency, nanoparticles of 50–100 nm displayed optimal DNA delivery activity. The application of an external magnetic field significantly enhanced the efficiency of nucleic acid delivery, with performance exceeding that of the commercially available lipid-based reagent, Lipofectamine 2000. The iron oxide nanoparticle delivery platform developed here offers the potential for magnetically guided targeting, as well as an opportunity to combine gene therapy with MRI imaging and magnetic hyperthermia.National Heart, Lung, and Blood InstituteNational Institutes of Health (U.S.) (Program of Excellence in Nanotechnology (PEN) Award, Contract #HHSN268201000045C