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In streams, phototrophic biofilms are considered to be a good‐quality resource for consumers and are essential to support secondary production. However, with the increasing occurrence of flow intermittency as a consequence of global climate change, limited information exists regarding the impact of drying and rewetting events on biofilm nutritional quality indicators and their consequences for consumers. This study aims at understanding how river intermittency affects the nutritional quality of phototrophic biofilms. Specifically, we examine the effects of drying and rewetting events on their capacity to support secondary production.Our hypothesis was that the capacity of biofilms to support secondary production relies on their nutritional quality: biofilms characterised by higher contents of long‐chain fatty acids, nitrogen and phosphorus are expected to provide a better‐quality resource for consumers. We also hypothesised that the nutritional quality of biofilms undergoes changes over time during drying events, and that these changes are influenced by their initial algal composition. This is because the algal composition within biofilms may shift in response to drying events, subsequently impacting the nutritional quality of the biofilms.We grew four phototrophic biofilms in flowing water, each with a different nutritional quality, and then exposed them to a short (3 days) or a long dry period (14 days). Biofilms were sampled 3 days and 18 days after rewetting (post‐disturbance and post‐recovery) to assess alterations in nutritional indicators relative to their pre‐disturbance state through pigment, fatty acid and stoichiometric analyses. We fed these biofilms to Gammarids (Gammarus fossarum) for 29 days and measured individual growth, feeding rate and locomotor activity. We also calculated a secondary production index to assess the biofilms' capacity to support higher trophic levels.Our findings revealed that the nutritional quality of biofilms was significantly reduced during the post‐disturbance phase. The duration of the dry period had minimal effect on this decline. Subsequently, during the recovery phase, nutritional quality indicators improved for biofilms initially dominated by cyanobacteria, while they either remained unchanged or decreased for biofilms initially dominated by diatoms, in comparison to the pre‐disturbance state. As a result, biofilms that initially exhibited a high nutritional quality were disrupted by the dry period, depending on the duration. However, the overall effects of dry period on gammarid's response and on secondary production were less pronounced, which is likely to have resulted from changes in the quantity of available resources.Our study demonstrates that a disturbance can modify the expected and effective qualities of biofilms. It highlights that biochemical parameters cannot reliably predict biofilm capacity to support secondary production. Biofilm history of disturbance, among other parameters, must be taken into account. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This paper presents a survey registration framework to assist in the recurrent inspection of a natural environment. Our framework coarsely aligns surveys at the image-level using visual simultaneous localization and mapping (SLAM), and it registers images at the pixel-level using SIFT Flow, which enables rapid manual inspection. The variation in appearance of natural environments makes data association a primary challenge of this work. We discuss this and other challenges, including 1) alternative approaches for coarsely aligning surveys of a natural environment, 2) how to select which images to compare between two surveys, and 3) strategies to boost image registration accuracy. We evaluate each stage of our approach, emphasizing alignment accuracy and stability with respect to large seasonal variations. Our domain is lakeshore monitoring, in which an autonomous surface vessel surveyed a 1-km lakeshore 33 times in 14 months. Our results show that our framework precisely aligns a significant number of images between surveys captured up to roughly three months apart, often across marked variation in appearance. Using these results, a human was able to spot several changes between surveys that would have otherwise gone unnoticed. [ABSTRACT FROM AUTHOR]

Short-term changes in temporal and spatial distributions of the toxic cyanobacterium Planktothrix rubescens in Lake Zurich were investigated using high-resolution data sets acquired with an autonomous surface vessel (ASV). Data profiles were recorded with a multi-parameter probe while the ASV navigated along 1.5 km toward a waypoint located on the other side of the lake by using a global positioning system. We deployed the ASV seven times on five consecutive days during the stratification period (July 2011) to generate cross-sectional views of temperature, light, oxygen, and phycoerythrin and chlorophyll fluorescence from surface to 18 m. The data were also used to compute daily photosynthetic rates. Data showed a daily reshaping of the P. rubescens distribution in the metalimnion on both horizontal and vertical axes, from patches to a shore-to-shore spreading. A thermocline depression observed after 16 h of sustained winds forced the accumulation of P. rubescens on the downwind shore. The compression of the metalimnion and its downward shift by 6 m within 24 h suggested the modulation of a longitudinal seiche following the wind event. This passive transport of the metalimnetic P. rubescens population resulted in a 90% light reduction, and a decrease of the averaged daily photosynthetic rate from ±21 mmol O2m-2 d-1 to -10 mmol O2 m-2 d-1. Negative photosynthetic rates were computed on 2 d out of 5 d, meaning that the transport of P. rubescens by seiches significantly affected the balance between oxygen production and utilization in Lake Zurich, especially because it is the dominant primary producer. [ABSTRACT FROM AUTHOR]

Owing to the fundamental nature of all-terrain exploration, autonomous rovers are confronted with unknown environments. This is especially apparent regarding soil interactions, as the nature of the soil is typically unknown. This work aims at establishing a framework from which the rover can learn from its interaction with the terrains encountered and shows the importance of such a method. We introduce a set of rover–terrain interaction (RTI) and remote data metrics that are expressed in different subspaces. In practice, the information characterizing the terrains, obtained from remote sensors (e.g., a camera) and local sensors (e.g., an inertial measurement unit) is used to characterize the respective remote data and RTI model. In each subspace, which can be described as a feature space encompassing either a remote data measurement or an RTI, similar features are grouped to form classes, and the probability distribution function over the features is learned for each one of those classes. Subsequently, data acquired on the same terrain are used to associate the corresponding models in each subspace and to build an inference model. Based on the remote sensor data measured, the RTI model is predicted using the inference model. This process corresponds to a near-to-far approach and provides the most probable RTI metrics of the terrain lying ahead of the rover. The predicted RTI metrics are then used to plan an optimal path with respect to the RTI model and therefore influence the rover trajectory. The CRAB rover is used in this work for the implementation and testing of the approach, which we call rover–terrain interactions learned from experiments (RTILE). This article presents RTILE, describes its implementation, and concludes with results from field tests that validate the approach. © 2009 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Tractor-trailer reversing is a classical nonlinear control problem in which many of the solutions proposed in the literature perform poorly in the presence of real-world constraints such as steering angle, rate limits, and lags. In this paper we describe a new method in which an inner loop controls the hitch angle of the trailer, creating a virtual articulated vehicle to which existing control techniques can be applied. We provide an analysis of the stability and convergence properties of this control approach, as well as experimental results that illustrate the robustness of this approach to model estimation errors, low-level control loop dynamics, and other disturbances introduced by, for example, state estimation errors. © 2008 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Hot metal carriers (HMCs) are large forklift-type vehicles used to move molten metal in aluminum smelters. This paper reports on field experiments that demonstrate that HMCs can operate autonomously and in particular can use vision as a primary sensor to locate the load of aluminum. We present our complete system but focus on the vision system elements and also detail experiments demonstrating reliable operation of the materials handling task. Two key experiments are described, lasting 2 and 5 h, in which the HMC traveled 15 km in total and handled the load 80 times. © 2008 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

An introduction to the journal is presented which discusses various reports within the issue on topics including algorithm for determining the alignment between Doppler sonar velocity sensors and attitude sensors for underwater robots, calibration problem for underwater robots, and multi-modal sensor calibration using a gradient orientation measure.

The article discusses various reports published within the issue, including one about a new way to model the behavior of multiple agents seen as coupled dynamic systems, about problems of localizing robotic platform and about addressing the problem of planning trajectories for fast vehicles moving in a complex environment.