Robotic weed control using automated weed and crop classification

Autonomous robotic weeding systems in precision farming have demonstrated their full potential to alleviate the current dependency on agrochemicals such as herbicides and pesticides, thus reducing environmental pollution and improving sustainability. However, most previous works require fast and constant‐time weed detection systems to achieve real‐time treatment, which forecloses the implementation of more capable but time‐consuming algorithms, for example, learning‐based methods. In this paper, a nonoverlapping multicamera system is applied to provide flexibility for the weed control system in dealing with the indeterminate classification delays. The design, implementation, and testing of our proposed modular weed control unit with mechanical and chemical weeding tools are presented. A framework that performs naive Bayes filtering, 3D direct intra‐ and inter‐camera visual tracking, and predictive control, while integrating state‐of‐the‐art crop/weed detection algorithms, is developed to guide the tools to achieve high‐precision weed removal. The experimental results show that our proposed fully operational weed control system is capable of performing selective mechanical as well as chemical in‐row weeding with indeterminate detection delays in different terrain conditions and crop growth stages.     

Visual model‐predictive localization for computationally efficient autonomous racing of a 72‐g drone

Drone racing is becoming a popular e‐sport all over the world, and beating the best human drone race pilots has quickly become a new major challenge for artificial intelligence and robotics. In this paper, we propose a novel sensor fusion method called visual model‐predictive localization (VML). Within a small time window, VML approximates the error between the model prediction position and the visual measurements as a linear function. Once the parameters of the function are estimated by the RANSAC algorithm, this error model can be used to compensate the prediction in the future. In this way, outliers can be handled efficiently and the vision delay can also be compensated efficiently. Theoretical analysis and simulation results show the clear advantage compared with Kalman filtering when dealing with the occasional large outliers and vision delays that occur in fast drone racing. Flight tests are performed on a tiny racing quadrotor named “Trashcan,” which was equipped with a Jevois smart camera for a total of 72 g. An average speed of 2 m/s is achieved while the maximum speed is 2.6 m/s. To the best of our knowledge, this flying platform is currently the smallest autonomous racing drone in the world, while still being one of the fastest autonomous racing drones.     

Robotic technologies for solar‐powered UAVs: Fully autonomous updraft‐aware aerial sensing for multiday search‐and‐rescue missions

Large‐scale aerial sensing missions can greatly benefit from the perpetual endurance capability provided by high‐performance low‐altitude solar‐powered unmanned aerial vehicles (UAVs). However, today these UAVs suffer from small payload capacity, low energetic margins, and high operational complexity. To tackle these problems, this paper presents four individual technical contributions and integrates them into an existing solar‐powered UAV system: First, a lightweight and power‐efficient day/night‐capable sensing system is discussed. Second, means to optimize the UAV platform to the specific payload and to thereby achieve sufficient energetic margins for day/night flight with payload are presented. Third, existing autonomous launch and landing functionality is extended for solar‐powered UAVs. Fourth, as a main contribution an extended Kalman filter (EKF)‐based autonomous thermal updraft tracking framework is developed. Its novelty is that it allows the end‐to‐end integration of the thermal‐induced roll moment into the estimation process. It is assessed against unscented Kalman filter and particle filter methods in simulation and implemented on the aircraft's low‐power autopilot. The complete system is verified during a 26 h search‐and‐rescue aerial sensing mock‐up mission that represents the first‐ever fully autonomous perpetual endurance flight of a small solar‐powered UAV with a day/night‐capable sensing payload. It also represents the first time that solar‐electric propulsion and autonomous thermal updraft tracking are combined in flight. In contrast to previous work that has focused on the energetic feasibility of perpetual flight, the individual technical contributions of this paper are considered core functionality to guarantee ease‐of‐use, effectivity, and reliability in future multiday aerial sensing operations with small solar‐powered UAVs.     

One-bit quantization is good for programmable coding metasurfaces

Science China Information Sciences -     

An Approximation Framework for Solvers and Decision Procedures

We consider the problem of automatically and efficiently computing models of constraints, in the presence of complex background theories such as floating-point arithmetic. Constructing models, or proving that a constraint is unsatisfiable, has various applications, for instance for automatic generation of test inputs. It is well-known that a naïve encoding of constraints into simpler theories (for instance, bit-vectors or propositional logic) often leads to a drastic increase in size, or that it is unsatisfactory in terms of the resulting space and runtime demands. We define a framework for systematic application of approximations in order to improve performance. Our method is more general than previous techniques in the sense that approximations that are neither under- nor over-approximations can be used, and it shows promising performance on practically relevant benchmark problems.     

Timed-automata abstraction of switched dynamical systems using control invariants

The development of formal methods for control design is an important challenge with potential applications in a wide range of safety-critical cyber-physical systems. Focusing on switched dynamical systems, we propose a new abstraction, based on time-varying regions of invariance (control funnels), that models behaviors of systems as timed automata. The main advantage of this method is that it allows for the automated verification and reactive controller synthesis without discretizing the evolution of the state of the system. Efficient and analytic constructions are possible in the case of linear dynamics whereas bounding funnels with conjectured properties based on numerical simulations can be used for general nonlinear dynamics. We demonstrate the potential of our approach with three examples.     

New insight into the interaction of sulfur with diesel NOx storage catalysts

A commercial NO_x-storage catalyst (NSC) has been subjected to different aging procedures on the engine bench simulating 100,000 km mileage. The aging consisted of cyclical sulfur exposure, subsequent sulfur removal and testing of the catalytic activity. More aggressive desulfation procedures result in more efficient sulfur removal and consequently good high temperature NO_x-conversion. However, low temperature NO_x-performance is lower than for agings employing more moderate desulfation conditions.

Sulfur post mortem analyses reveal a slight decrease of residual sulfur concentration over the length of all catalysts after completion of the aging. BET and CO-chemisorption data are in line with the increase of temperature from catalyst inlet to outlet during the desulfation. The conversion of BaCO₃ to BaSO₄ during the sulfur poisoning was followed by IR, TPD and TPR. A quantitative analysis of the data shows that at the end of the agings all residual sulfur is mainly located at barium sites as opposed to other oxide components like e.g. alumina or ceria. TPR data suggest that prolonged rich purges of the sulfated catalyst lead to an efficient decomposition of sulfates however some sulfur is being trapped in the form of BaS which seems difficult to remove under constant rich conditions.

XPS data suggest that the bulk sulfur amounts in the catalyst may be decoupled from the actual concentration at the catalyst surface. In that sense, the residual sulfur concentration might be limited in some cases as a criterion to assess the performance of a NSC. More reducing desulfation conditions cause the residual sulfur to be present in the form of more reduced sulfur species (sulfites, sulfides) on the catalyst.     

Biocatalytic Synthesis of Nitriles through Dehydration of Aldoximes: The Substrate Scope of Aldoxime Dehydratases

Nitriles, which are mostly needed and produced by the chemical industry, play a major role in various industry segments, ranging from high‐volume, low‐price sectors, such as polymers, to low‐volume, high‐price sectors, such as chiral pharma drugs. A common industrial technology for nitrile production is ammoxidation as a gas‐phase reaction at high temperature. Further popular approaches are substitution or addition reactions with hydrogen cyanide or derivatives thereof. A major drawback, however, is the very high toxicity of cyanide. Recently, as a synthetic alternative, a novel enzymatic approach towards nitriles has been developed with aldoxime dehydratases, which are capable of converting an aldoxime in one step through dehydration into nitriles. Because the aldoxime substrates are easily accessible, this route is of high interest for synthetic purposes. However, whenever a novel method is developed for organic synthesis, it raises the question of substrate scope as one of the key criteria for application as a “synthetic platform technology”. Thus, the scope of this review is to give an overview of the current state of the substrate scope of this enzymatic method for synthesizing nitriles with aldoxime dehydratases. As a recently emerging enzyme class, a range of substrates has already been studied so far, comprising nonchiral and chiral aldoximes. This enzyme class of aldoxime dehydratases shows a broad substrate tolerance and accepts aliphatic and aromatic aldoximes, as well as arylaliphatic aldoximes. Furthermore, aldoximes with a stereogenic center are also recognized and high enantioselectivities are found for 2‐arylpropylaldoximes, in particular. It is further noteworthy that the enantiopreference depends on the E and Z isomers. Thus, opposite enantiomers are accessible from the same racemic aldehyde and the same enzyme.     

Trimethyl Lock: A Multifunctional Molecular Tool for Drug Delivery,Cellular Imaging,and Stimuli‐Responsive Materials

Trimethyl lock (TML) systems are based on ortho‐hydroxydihydrocinnamic acid derivatives displaying increased lactonization reactivity owing to unfavorable steric interactions of three pendant methyl groups, and this leads to the formation of hydrocoumarins. Protection of the phenolic hydroxy function or masking of the reactivity as benzoquinone derivatives prevents lactonization and provides a trigger for controlled release of molecules attached to the carboxylic acid function through amides, esters, or thioesters. Their easy synthesis and possible chemical adaption to several different triggers make TML a highly versatile module for the development of drug‐delivery systems, prodrug approaches, cell‐imaging tools, molecular tools for supramolecular chemistry, as well as smart stimuliresponsive materials.