Implementation of mmWave long-range backhaul for UAV-BS

Uncrewed aerial vehicles (UAVs) have become a vital element in nonterrestrial networks, especially with respect to 5G communication systems and beyond. The use of UAVs in support of 4G/5G base station (uncrewed aerial vehicle base station [UAV-BS]) has proven to be a practical solution for extending cellular network services to areas where conventional infrastructures are unavailable. In this study, we introduce a UAV-BS system that utilizes a high-capacity wireless backhaul operating in millimeter-wave frequency bands. This system can achieve a maximum throughput of 1.3 Gbps while delivering data at a rate of 300 Mbps, even at distances of 10 km. We also present the details of our testbed implementation alongside the performance results obtained from field tests.     

Silver Nanoflower Decorated Graphene Oxide Sponges for Highly Sensitive Variable Stiffness Stress Sensors

Soft conductive materials should enable large deformation while keeping high electrical conductivity and elasticity. The graphene oxide (GO)‐based sponge is a potential candidate to endow large deformation. However, it typically exhibits low conductivity and elasticity. Here, the highly conductive and elastic sponge composed of GO, flower‐shaped silver nanoparticles (AgNFs), and polyimide (GO‐AgNF‐PI sponge) are demonstrated. The average pore size and porosity are 114 µm and 94.7%, respectively. Ag NFs have thin petals (8–20 nm) protruding out of the surface of a spherical bud (300–350 nm) significantly enhancing the specific surface area (2.83 m² g^?1). The electrical conductivity (0.306 S m^?1 at 0% strain) of the GO‐AgNF‐PI sponge is increased by more than an order of magnitude with the addition of Ag NFs. A nearly perfect elasticity is obtained over a wide compressive strain range (0–90%). The strain‐dependent, nonlinear variation of Young's modulus of the sponge provides a unique opportunity as a variable stiffness stress sensor that operates over a wide stress range (0–10 kPa) with a high maximum sensitivity (0.572 kPa^?1). It allows grasping of a soft rose and a hard bottle, with the minimal object deformation, when attached on the finger of a robot gripper.     

Electrophysicochemical characteristics of a waterpen point coronadischarge

Some interesting electrophysicochemical characteristics of waterpen point-to-plate discharges with DC and AC power have been investigated in a room atmosphere. The metal point electrode of a conventional point-to-plate air gap is severely bombarded by energetic ions from the discharge region near the point. Concurrently, the temperature of the point is greatly increased. There are different characteristics for the waterpen point discharge, because the surface temperature of the waterpen point stays low due to the evaporation of the moisture from the waterpen point. In this paper, the discharges and electrophysicochemical characteristics of a waterpen point and a Pt metal point have been studied to evaluate the differences. It was found that mists and sprays are dispersed from the waterpen point due to the bombardment of ions. Also, a positive corona is effective for mist dispersion, a negative corona disperses sprays, and AC corona disperses both mists and sprays. The AC discharge of the waterpen point generated more ozone of 56 ppm, while it was the negative DC discharge of the Pt point that produced more ozone of 30 ppm. The AC discharge of the waterpen point produced 0.11 ppm at 10 kV, and the Pt point produced 0.10 ppm at 15 kV. The DC discharge of the both points showed no NO formation     

Localization of an unmanned ground vehicle based on hybrid 3D registration of 360 degree range data and DSM

A computer vision technique to identify the location of an outdoor unmanned ground vehicle (UGV) is presented. The proposed technique is based on hybrid 3D registration of 360 degree laser range data to a digital surface model (DSM). Range frames obtained from 48 laser detectors are aligned with the reference coordinate system of the DSM. Three novel approaches are proposed for accurate and fast 3D registration of range data and the DSM. First, a two-step hybrid 3D registration technique is proposed. A pair-wise registration step of two consecutive range frames is followed by a refinement step using a layered DSM. Second, a fast projection-based pair-wise registration is proposed by employing rasterized 360 degree range frames. Third, a high elevation DSM is divided into several elevation layers and correspondence search is done near the vehicle’s current elevation. This reduces the number of matching outliers and facilitates fast localization. Experimental results show that the proposed approaches yield better performance in 3D localization compared to conventional 3D registration techniques. Error analysis on five outdoor paths is presented with respect to ground truth.     

Localization algorithm using a virtual label for a mobile robot in indoor and outdoor environments

Scanning laser range sensors provide range data consisting of a set of point measurements. The laser sensor URG-04LX has a distance range of approximately 0.02–4 m and a scanning angle range of 240°. Usually, such an image range is acquired from one viewpoint by “moving” the laser beam using rotating mirrors/prisms. The orientation of the laser beam can easily be measured and converted into the coordinates of the image. This article conducts localization using virtual labels with data about distances in the environment obtained from 2D distance laser sensors. This method puts virtual labels on special features and points which are along the mobile robot’s path. The current location is calculated by combining the virtual label and the range image of the laser range finder.     

Redundant multicast routing in multilayer networks with shared risk resource groups: Complexity,models and algorithms

This paper presents a redundant multicast routing problem in multilayer networks that arises from large-scale distribution of realtime multicast data (e.g., Internet TV, videocasting, online games, stock quotes). Since these multicast services commonly operate in multilayer networks, the communications paths need to be robust against a single router or link failure as well as multiple such failures due to shared risk link groups (SRLGs). The main challenge of this multicast is to ensure the service availability and reliability using a path protection scheme, which is to find a redundant path that is SRLG-disjoint (diverse) from each working path. The objective of this problem is, therefore, to find two redundant multicast trees, each from one of the two redundant sources to every destination, at a minimum total communication cost whereas two paths from the two sources to every destination are guaranteed to be SRLG-diverse (i.e., links in the same risk group are disjoint). In this paper, we present two new mathematical programming models, edge-based and path-based, for the redundant multicast routing problem with SRLG-diverse constraints. Because the number of paths in path-based model grows exponentially with the network size, it is impossible to enumerate all possible paths in real life networks. We develop three approaches (probabilistic, non-dominated and nearly non-dominated) to generate potentially good paths that may be included in the path-based model. This study is motivated by emerging applications of internet-protocol TV service, and we evaluate the proposed approaches using real life network topologies. Our empirical results suggest that both models perform very well, and the nearly non-dominated path approach outperforms all other path generation approaches.     

Pattern recognition using feature feedback: Application to face recognition

In this paper, we propose a new pattern recognition method using feature feedback and present its application to face recognition. Conventional pattern recognition methods extract the features employed for classification using PCA, LDA and so on. On the other hand, in the proposed method, the extracted features are analyzed in the original space using feature feedback. Using reverse mapping from the extracted features to the original space, we can identify the important part of the original data that affects the classification. In this way, we can modify the data to obtain a higher classification rate, make it more compact or abbreviate the required sensors. To verify the applicability of the proposed method, we apply it to face recognition using the Yale Face Database. Each face image is divided into two parts, the important part and unimportant part, using feature feedback, and the classification performed using the feature mask obtained from feature feedback. Also, we combine face recognition with image compression. The experimental results show that the proposed method works well.     

Improving traversability of quadruped walking robots using body movement in 3D rough terrains

This paper presents a study on improving the traversability of a quadruped walking robot in 3D rough terrains. The key idea is to exploit body movement of the robot. The position and orientation of the robot are systematically adjusted and the possibility of finding a valid foothold for the next swing is maximized, which makes the robot have more chances to overcome the rough terrains. In addition, a foothold search algorithm that provides the valid foothold while maintaining a high traversability of the robot, is investigated and a gait selection algorithm is developed to help the robot avoid deadlock situations. To explain the algorithms, new concepts such as reachable area, stable area, potential search direction, and complementary kinematic margin are introduced, and the effectiveness of the algorithms is validated via simulations and experiments.