Aerial photogrammetry of seabirds from digital aerial video images using relative change in size to estimate flight height

Calculating the height at which birds fly over the sea is a challenging task but remains important to assessing collision risk in proposed offshore windfarm areas for consenting purposes. This could be done by several methods (e.g., GPS or laser range-finders), but each have biases that make it difficult to generate site-wide assessments. Digital video aerial surveys, which quickly cover large areas, were used to assess flight heights of northern gannets and black-legged kittiwakes using a photogrammetric technique combined with a semi-automated measurement tool. The lengths of birds known to be at sea surface as identified by reflection on the water, were compared to lengths of birds at unknown height to generate individual flight height profiles. Validation of the flight height method using objects of known dimensions and heights suggested a 9 – 18% error (3 – 6 m at ~30 m height). However, the profiles of mean flight height distribution matched patterns in previous work. This method was able to estimate the flying heights of 65% and 75% of flying gannets and kittiwakes respectively in this case study. The annual percentage of gannets at collision risk height for a set of turbines with a 30m air gap was estimated at 29.8%, and 16.1% for kittiwake. This technique can greatly improve our knowledge of the spatial distribution of flight height patterns in marine ecosystems, but also allows stakeholders to assess collision risk more easily within the sphere of offshore wind for the consenting process.

Gap Traversing Motion via a Hexapod Tracked Mobile Robot Based on Gap Width Detection

The authors developed a hexapod tracked mobile robot: a tracked mobile robot which is equipped with six legs attached to the robot’s body. In a transportation task, this robot can traverse a wide gap by supporting track driving with four front and rear legs while holding the target object with its two middle legs. To realize autonomous actions with this robot, we developed a two-dimensional distance measurement system using an infrared sensor. This system is very simple, with the sensor attached to a servomotor, such that it does not require high computing power for measurement. In addition, the system can be equipped at a lower cost than laser range finders and depth cameras. This paper describes the selection of the gap traversing mode according to gap width detected by the system. In this study, we conducted a gap width detection experiment and an autonomous gap traversing experiment using the hexapod tracked mobile robot with the proposed system. The obtained results confirm the effectiveness of the proposed system and autonomous traversing, which corresponds with the gap width detection.

Kovalev passive rangefinder

The authors present the results of longtime research on the development and improvement of a passive geodetic rangefinder based on the inbasis method of distance measurement. Actually, active laser range finders are not always effective at field works. An original compact optical scheme of a passive rangefinder based on a theodolite telescope and a mould photo receiver with application of digital methods for coordinate calculation is proposed. The distance and dimensions of the object are defined. The former is identified by the shift between the images on the horizontal axis. The merit of such a system is the absence of mechanical displacements. Its main advantage is an extremely simple optical path. The technical result is reduction in overall dimensions and weight, while maintaining an acceptable error in the passive range measurement. The use of Kovalev passive rangefinder is promising at performing geodetic measurements with total stations. There is also a description of the rangefinder sample as well as the calculations results according to the distance measurement accuracy.

OSPREY

Tire wear is a leading cause of accidents. Tire wear is measured either manually, or by embedding sensors in tires, or using off-tire sensors. Manual sensing is extremely tedious. Sensors embedded in tire treads are challenging to design and expensive to embed. Off-tire sensors like laser range finders are prone to debris that may settle in grooves. To overcome these shortcomings, we propose a mmWave radar based tire wear sensor, which is easy to install, and continuously provides accurate and robust tire wear measurements even in the presence of debris.

Comparison of 3D Point Clouds Obtained by Terrestrial Laser Scanning and Personal Laser Scanning on Forest Inventory Sample Plots

In forest inventory, trees are usually measured using handheld instruments; among the most relevant are calipers, inclinometers, ultrasonic devices, and laser range finders. Traditional forest inventory has been redesigned since modern laser scanner technology became available. Laser scanners generate massive data in the form of 3D point clouds. We have developed a novel methodology to provide estimates of the tree positions, stem diameters, and tree heights from these 3D point clouds. This dataset was made publicly accessible to test new software routines for the automatic measurement of forest trees using laser scanner data. Benchmark studies with performance tests of different algorithms are welcome. The dataset contains co-registered raw 3D point-cloud data collected on 20 forest inventory sample plots in Austria. The data were collected by two different laser scanning systems: (1) A mobile personal laser scanner (PLS) (ZEB Horizon, GeoSLAM Ltd., Nottingham, UK) and (2) a static terrestrial laser scanner (TLS) (Focus3D X330, Faro Technologies Inc., Lake Mary, FL, USA). The data also contain digital terrain models (DTMs), field measurements as reference data (ground-truth), and the output of recent software routines for the automatic tree detection and the automatic stem diameter measurement.

ARENA—Augmented Reality to Enhanced Experimentation in Smart Warehouses

The current industrial scenario demands advances that depend on expensive and sophisticated solutions. Augmented Reality (AR) can complement, with virtual elements, the real world. Faced with this features, an AR experience can meet the demand for prototype testing and new solutions, predicting problems and failures that may only exist in real situations. This work presents an environment for experimentation of advanced behaviors in smart factories, allowing experimentation with multi-robot systems (MRS), interconnected, cooperative, and interacting with virtual elements. The concept of ARENA introduces a novel approach to realistic and immersive experimentation in industrial environments, aiming to evaluate new technologies aligned with the Industry 4.0. The proposed method consists of a small-scale warehouse, inspired in a real scenario characterized in this paper, managing by a group of autonomous forklifts, fully interconnected, which are embodied by a swarm of tiny robots developed and prepared to operate in the small scale scenario. The AR is employed to enhance the capabilities of swarm robots, allowing box handling and virtual forklifts. Virtual laser range finders (LRF) are specially designed as segmentation of a global RGB-D camera, to improve robot perception, allowing obstacle avoidance and environment mapping. This infrastructure enables the evaluation of new strategies to improve manufacturing productivity, without compromising the production by automation faults.

ClusterMap Building and Relocalization in Urban Environments for Unmanned Vehicles

Map building and map-based relocalization techniques are important for unmanned vehicles operating in urban environments. The existing approaches require expensive high-density laser range finders and suffer from relocalization problems in long-term applications. This study proposes a novel map format called the ClusterMap, on the basis of which an approach to achieving relocalization is developed. The ClusterMap is generated by segmenting the perceived point clouds into different point clusters and filtering out clusters belonging to dynamic objects. A location descriptor associated with each cluster is designed for differentiation. The relocalization in the global map is achieved by matching cluster descriptors between local and global maps. The solution does not require high-density point clouds and high-precision segmentation algorithms. In addition, it prevents the effects of environmental changes on illumination intensity, object appearance, and observation direction. A consistent ClusterMap without any scale problem is built by utilizing a 3D visual–LIDAR simultaneous localization and mapping solution by fusing LIDAR and visual information. Experiments on the KITTI dataset and our mobile vehicle illustrates the effectiveness of the proposed approach.

A calibration method of dual two-dimensional laser range finders for mobile manipulator

In this article, a method for calibrating the relative position between dual two-dimensional laser range finders is proposed. This relative position is affected by the manufacture or assembling error of mobile platform, and this error could reduce the accuracy of localization. This article focuses on three-degree-of-freedom calibration, that is, one rotational and two translational degrees of freedom. The entire calibration process can be summed up into three steps. The first step is to allow the dual finders to scan one corner at the same time and then extract the parameters of the corner. The second step is to establish a cost function which is established according to the direction vector of the line and the repeatability of the corners. With this function, the genetic algorithm is used to obtain the final calibration result. Moreover, the finder systematic error and the statistical error are also considered into this article. Simulations and experiments are carried out to verify the proposed method.