This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.

Coverage control for mobile sensing networks

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

Induction heating (IH) technology is nowadays the heating technology of choice in many industrial, domestic, and medical applications due to its advantages regarding efficiency, fast heating, safety, cleanness, and accurate control. Advances in key technologies, i.e., power electronics, control techniques, and magnetic component design, have allowed the development of highly reliable and cost-effective systems, making this technology readily available and ubiquitous. This paper reviews IH technology summarizing the main milestones in its development and analyzing the current state of art of IH systems in industrial, domestic, and medical applications, paying special attention to the key enabling technologies involved. Finally, an overview of future research trends and challenges is given, highlighting the promising future of IH technology.

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Induction Heating Technology and Its Applications: Past Developments, Current Technology, and Future Challenges

https://www.fs.fed.us/nrs/pubs/jrnl/2013/nrs_2013_dandios_001.pdf

High spatial resolution three-dimensional mapping of vegetation spectral dynamics using computer vision

Lecture notes in control and information sciences

Revolution symmetry is a realistic assumption for modelling the majority of catadioptric and dioptric cameras. In central systems it can be described by a projection model based on radially symmetric distortion. In these systems straight lines are projected on curves called line-images. These curves have in general more than two degrees of freedom and their shape strongly depends on the particular camera configuration. Therefore, the existing line-extraction methods for this kind of omnidirectional cameras require the camera calibration by contrast with the perspective case where the calibration is not involved in the shape of the projected line-image. However, this drawback can be considered as an advantage because the shape of the line-images can be used for self-calibration. In this paper, we present a novel method to extract line-images in uncalibrated omnidirectional images which is valid for radially symmetric central systems. In this method we propose using the plumb-line constraint to find closed form solutions for different types of camera systems, dioptric or catadioptric. The inputs of the proposed method are points belonging to the line-images and their intensity gradient. The gradient information allows to reduce the number of points needed in the minimal solution improving the result and the robustness of the estimation. The scheme is used in a line-image extraction algorithm to obtain lines from uncalibrated omnidirectional images without any assumption about the scene. The algorithm is evaluated with synthetic and real images showing good performance. The results of this work have been implemented in an open source Matlab toolbox for evaluation and research purposes.

Automatic Line Extraction in Uncalibrated Omnidirectional Cameras with Revolution Symmetry

In this paper we tackle the problem of persistent coverage, where a team of agents covers an area whose amount of coverage degrades with time. The task is never accomplished completely due to the coverage decay and the agents have to revisit the domain persistently. In this framework, our contribution is a novel approach which consists not only in developing efficient motion to perform the coverage, but also in covering the domain with a variable coverage action. The agents can adapt its coverage power to the coverage error of the actuator domain, being able to reduce the energy consumption and the coverage error. We propose a new controller for the coverage power and we demonstrate by means of simulations that it is more efficient and flexible than developing the coverage with constant power.

Persistent coverage control with variable coverage action in multi-robot environment

This paper proposes a novel kind of adaptive observer called reset adaptive observer (ReO). A ReO is an adaptive observer consisting of an integrator and a reset law that resets the output of the integrator depending on a predefined condition. The main contribution of this paper is the application of the reset element theory to the adaptive observer LTI framework. The introduction of the reset element in the adaptive laws can decrease the overshooting and settling time of the estimation process without sacrificing the rising time. The stability and convergence LMI-based analysis of the proposed ReO is also addressed. Additionally, an easily computable method to determine the ℒ 2 gain of the ReO dealing with noise-corrupted systems is presented. A simulation example shows the potential benefit of the proposed reset adaptive observer.

Reset adaptive observers and stability properties

Addressing the problem of enclosing and tracking a target requires multiple agents with adequate motion strategies. We consider a team of unicycle robots with a standard camera on board. The robots must maintain the desired enclosing formation while dealing with their nonholonomic motion constraints. The reference formation trajectories must also guarantee permanent visibility of the target by overcoming the limited field of view of the cameras. In this article, we present a novel approach to characterize the conditions on the robots’ trajectories taking into account the motion and visual constraints. We also propose online and offline motion planning strategies to address the constraints involved in the task of enclosing and tracking the target. These strategies are based on maintaining the formation shape with variable size or, alternatively, on maintaining the size of the formation with flexible shape.

Adaptive Multirobot Formation Planning to Enclose and Track a Target With Motion and Visibility Constraints

This paper deals with the computation of homographies from two views in a multi-plane scene. In the general case, homographies can be determined using four matched points or lines belonging to planes. We propose an alternative method when a first homography has been obtained, and then three matches are sufficient to compute a second homography. This process is based on the geometric constraint introduced by the first homography. In this work, the extraction and matching of features, points or lines, is automatically performed using robust techniques. Experimental results with synthetic data and real images show the advantages of this approach. Besides, the performance using points or lines as image features is compared.

/pdf/computing-homographies-from-three-lines-or-points-in-an-2idsia0hcu.pdf

Gonzalo López-Nicolás

Papers

Automatic Line Extraction in Uncalibrated Omnidirectional Cameras with Revolution Symmetry

Persistent coverage control with variable coverage action in multi-robot environment

Reset adaptive observers and stability properties

Adaptive Multirobot Formation Planning to Enclose and Track a Target With Motion and Visibility Constraints

Computing homographies from three lines or points in an image pair