Irregular Terrain Research Articles

Three-dimensional parabolic equation for infrasound propagation above topography

The parabolic equation (PE) is one of the most popular methods for the modeling of low-frequency sound in the atmosphere. Over the past decades, considerable efforts have been dedicated to the inclusion of medium inhomogeneities, such as wind and turbulence, extending the PE to more realistic atmospheric conditions. On the other hand, few models take topography into account, while its effects on infrasound propagation are important in some cases. A new development has enabled the inclusion of irregular terrain in the narrow-angle 3DPE for a moving inhomogeneous medium [Khodr et al., JASA (2020)]. A coordinate transform similar to the Beilis-Tappert mapping used in 2D [Parakkal et al., JASA (2012)] is introduced to account for the variation in topography. The numerical solution relies on a Crank–Nicolson implicit scheme along the propagating direction. The pressure field at every step is computed with an iterative fixed-point algorithm which consists of a succession of tridiagonal systems that can be efficiently solved. A validation is performed against 3D Boundary Element simulations for propagation above a Gaussian hill in a homogeneous atmosphere. The existence of transversal scattering in the shadow zone, not represented by 2D models, is highlighted. Further developments include the extension of the method to a split-step wide-angle formulation. [This work was conducted at the University of Bristol in partnership with AWE Blacknest.]

Development of Hexapod Robot with Computer Vision

Abstract: Nowadays many robotic systems are developed with lot of innovation, seeking to get flexibility and efficiency of biological systems. Hexapod Robot is the best example for such robots, it is a six-legged robot whose walking movements try to imitate the movements of the insects, it has two sets of three legs alternatively which is used to walk, this will provide stability, flexibility and mobility to travel on irregular surfaces. With these attributes the hexapod robots can be used to explore irregular surfaces, inhospitable places, or places which are difficult for humans to access. This paper involves the development of hexapod robot with digital image processing implemented on Raspberry Pi, to study in the areas of robotic systems with legged locomotion and robotic vision. This paper is an integration of a robotic system and an embedded system of digital image processing, programmed in high level language using Python. It is equipped with a camera to capture real time video and uses a distance sensor that allow the robot to detect obstacles. The Robot is Self-Stabilizing and can detect corners. The robot has 3 degrees of freedom in each six legs thus making a 18 DOF robotic movement. The use of multiple degrees of freedom at the joints of the legs allows the legged robots to change their movement direction without slippage. Additionally, it is possible to change the height from the ground, introducing a damping and a decoupling between the terrain irregularities and the body of the robot servo motors. Keywords: Hexapod, Raspberry Pi, Computer vision, Object detection, Yolo, Servo Motor, OpevCV.

A Redundant Configuration of Four Low-Cost GNSS-RTK Receivers for Reliable Estimation of Vehicular Position and Posture.

This paper proposes a low-cost sensor system composed of four GNSS-RTK receivers to obtain accurate position and posture estimations for a vehicle in real-time. The four antennas of the receivers are placed so that every three-antennas combination is optimal to get the most precise 3D coordinates with respect to a global reference system. The redundancy provided by the fourth receiver allows to improve estimations even more and to maintain accuracy when one of the receivers fails. A mini computer with the Robotic Operating System is responsible for merging all the available measurements reliably. Successful experiments have been carried out with a ground rover on irregular terrain. Angular estimates similar to those of a high-performance IMU have been achieved in dynamic tests.

Towards optimal toe-clearance in synthesizing polycentric prosthetic knee mechanism

Stability at the stance phase and near normal able-bodied swing phase kinematics are essential in designing the prosthetic knee mechanism for transfemoral amputees. Primarily, insufficient mid swing toe clearance results in asymmetrical gait patterns, leading to muscular-skeletal pain and joint degeneration. The present work is focused on synthesizing a polycentric knee mechanism to enhance the toe-clearance at mid-swing for safe level ground walking of amputees in developing countries. Both fixed and moving centrodes of the four-bar knee mechanism are considered in optimal synthesis of the mechanism for achieving able-bodied gait patterns using evolutionary algorithms in mechanism design software tools. The knee stability at heel contact, stabilizing moment at push-off, stable knee flexion range, maximum knee flexion and maximum toe-clearance at mid-swing are the parameters used for comparing the knee design with the existing commercially available designs. The optimized results are then verified experimentally by building a functional prototype using a 3 D printing technique. The designed mechanism executes nominal performance in four parameters and offers enhanced toe-clearance during mid-swing. This is a significant improvement over the existing designs for amputees to navigate comfortably on irregular terrain in developing countries.

A Flexible Multimodal Sole Sensor for Legged Robot Sensing Complex Ground Information during Locomotion.

Recent achievements in the field of computer vision, reinforcement learning, and locomotion control have largely extended legged robots’ maneuverability in complex natural environments. However, little research focuses on sensing and analyzing the physical properties of the ground, which is crucial to robots’ locomotion during their interaction with highly irregular profiles, deformable terrains, and slippery surfaces. A biomimetic, flexible, multimodal sole sensor (FMSS) designed for legged robots to identify the ontological status and ground information, such as reaction force mapping, contact situation, terrain, and texture information, to achieve agile maneuvers was innovatively presented in this paper. The FMSS is flexible and large-loaded (20 Pa–800 kPa), designed by integrating a triboelectric sensing coat, embedded piezoelectric sensor, and piezoresistive sensor array. To evaluate the effectiveness and adaptability in different environments, the multimodal sensor was mounted on one of the quadruped robot’s feet and one of the human feet then traversed through different environments in real-world tests. The experiment’s results demonstrated that the FMSS could recognize terrain, texture, hardness, and contact conditions during locomotion effectively and retrain its sensitivity (0.66 kPa−1), robustness, and compliance. The presented work indicates the FMSS’s potential to extend the feasibility and dexterity of tactile perception for state estimation and complex scenario detection.

LoRa Communications as an Enabler for Internet of Drones towards Large-Scale Livestock Monitoring in Rural Farms.

Currently, smart farming is considered an effective solution to enhance the productivity of farms; thereby, it has recently received broad interest from service providers to offer a wide range of applications, from pest identification to asset monitoring. Although the emergence of digital technologies, such as the Internet of Things (IoT) and low-power wide-area networks (LPWANs), has led to significant advances in the smart farming industry, farming operations still need more efficient solutions. On the other hand, the utilization of unmanned aerial vehicles (UAVs), also known as drones, is growing rapidly across many civil application domains. This paper aims to develop a farm monitoring system that incorporates UAV, LPWAN, and IoT technologies to transform the current farm management approach and aid farmers in obtaining actionable data from their farm operations. In this regard, an IoT-based water quality monitoring system was developed because water is an essential aspect in livestock development. Then, based on the Long-Range Wide-Area Network (LoRaWAN®) technology, a multi-channel LoRaWAN® gateway was developed and integrated into a vertical takeoff and landing drone to convey collected data from the sensors to the cloud for further analysis. In addition, to develop LoRaWAN®-based aerial communication, a series of measurements and simulations were performed under different configurations and scenarios. Finally, to enhance the efficiency of aerial-based data collection, the UAV path planning was optimized. Measurement results showed that the maximum achievable LoRa coverage when operating on-air via the drone is about 10 km, and the Longley–Rice irregular terrain model provides the most suitable path loss model for the scenario of large-scale farms, and a multi-channel gateway with a spreading factor of 12 provides the most reliable communication link at a high drone speed (up to 95 km/h). Simulation results showed that the developed system can overcome the coverage limitation of LoRaWAN® and it can establish a reliable communication link over large-scale wireless sensor networks. In addition, it was shown that by optimizing flight paths, aerial data collection could be performed in a much shorter time than industrial mission planning (up to four times in our case).

Glacial and periglacial geomorphology of central Troms and Finnmark county, Arctic Norway

ABSTRACT Here we present a glacial and periglacial geomorphological map of a ∼6800 km2 region of central Troms and Finnmark county, Arctic Norway. The map is presented at a 1:115,000 scale with the aim of characterising the spatial distribution of glacial and periglacial landforms and facilitating the reconstruction of the glacial history of the region during the latter stages of deglaciation from the Last Glacial Maximum and into the Holocene. Mapping was conducted predominantly by manual digitisation of landforms using a combination of Sentinel-2A/2B satellite imagery (10 m pixel resolution), vertical aerial photographs (<1 m pixel resolution), and Digital Elevation Models (10 and 2 m pixel resolution). Over 20,000 individual features have been mapped and include moraines (subdivided into major and minor moraines), ridges within areas of discrete debris accumulations (DDAs), flutings, eskers, irregular mounded terrain, lineations, glacially streamlined bedrock, possible glacially streamlined terrain, pronival ramparts, rock glaciers (subdivided into valley wall and valley floor, and rock glacierised moraines), lithalsas, contemporary glaciers and lakes. The map records several noteworthy large moraine assemblages within individual valleys, forming inset sequences from pre-Younger Dryas limits up to the 2018/19 ice margins and represents a valuable dataset for reconstructing Holocene glacial and periglacial activity.

ANALYSIS ON PREDICTION OF PATH LOSS FOR MOBILE NETWORK IN JNEC, DEWATHANG AT 1800 MHz

As the mobile cellular subscription is constantly increasing, the demand for good network and data traffic, remains to be high. In order to achieve that, proper network planning is important to enhance reliable mobile network and optimization. Path loss modelling is extensively used in the initial feasibility studies for the proper deployment of telecommunication. Prediction of path loss helps to indicates the field strength of the radio propagation. Path loss is the weakening of signal strength during propagation and can be determined by using different models. Largely affected by the complex terrain, buildings, trees, generally, the path loss is caused by reflection, refraction and diffraction. The evaluation is performed at 1800 MHz frequency which is the operating band of Long-Term Evolution (LTE) 4G network service in the region. A comparative study is done between different types of path loss models used in LTE networks in MATLAB. Analysis of path loss for irregular terrain in the region is also being simulated using Radio-mobile. With this study, a person can predict the mobile signal quality and a proper network can be planned.

High-Resolution Vertical Habitat Mapping of a Deep-Sea Cliff Offshore Greenland

Recent advances in deep-sea exploration with underwater vehicles have led to the discovery of vertical environments inhabited by a diverse sessile fauna. However, despite their ecological importance, vertical habitats remain poorly characterized by conventional downward-looking survey techniques. Here we present a high-resolution 3-dimensional habitat map of a vertical cliff hosting a suspension-feeding community at the flank of an underwater glacial trough in the Greenland waters of the Labrador Sea. Using a forward-looking set-up on a Remotely Operated Vehicle (ROV), a high-resolution multibeam echosounder was used to map out the topography of the deep-sea terrain, including, for the first time, the backscatter intensity. Navigational accuracy was improved through a combination of the USBL and the DVL navigation of the ROV. Multi-scale terrain descriptors were derived and assigned to the 3D point cloud of the terrain. Following an unsupervised habitat mapping approach, the application of a K-means clustering revealed four potential habitat types, driven by geomorphology, backscatter and fine-scale features. Using groundtruthing seabed images, the ecological significance of the four habitat clusters was assessed in order to evaluate the benefit of unsupervised habitat mapping for further fine-scale ecological studies of vertical environments. This study demonstrates the importance of a priori knowledge of the terrain around habitats that are rarely explored for ecological investigations. It also emphasizes the importance of remote characterization of habitat distribution for assessing the representativeness of benthic faunal studies often constrained by time-limited sampling activities. This case study further identifies current limitations (e.g., navigation accuracy, irregular terrain acquisition difficulties) that can potentially limit the use of deep-sea terrain models for fine-scale investigations.

Metric scale and angle estimation in monocular visual odometry with multiple distance sensors

In this paper, a novel approach is presented to estimate the metric scale (MSC) and roll and pitch angles of a platform by using distance sensors in a monocular visual odometry setup. A state-of-the-art visual odometry algorithm Semi-Direct Visual Odometry (SVO) [1] is used to obtain sparse three dimensional (3D) point cloud which is then matched with the measurements obtained from the distance sensors for the estimation process. Metric scale with Kalman (MSCwK) filter approach is presented where the metric scale parameter is modeled as a Gaussian random variable and updated with a Kalman filter to improve robustness and accuracy. Maximum Likelihood (ML) method is presented to include multiple distance sensors for a better metric scale estimation. The estimation of the roll and pitch angles for the camera platform is considered. This is achieved with respect to the ground plane using at least three distance sensors placed in a specific geometry to overcome ambiguity and obtain a unique solution. Proposed approach can handle terrain irregularities and does not have drift. Several simulations are performed and the performances of the proposed approaches are compared with the previous works and SVO. The experiments also include real data to show the practical relevance. It is shown that the proposed approaches improve both the metric scale and roll and pitch angles significantly.

On the Use of UTD-Based Models for RF Path Loss Prediction Due to Diffraction on a Forest-Covered Ridge

Irregular terrains covered with forest vegetation represent a challenging scenario for radio planning. A case of particular interest is the one where a forest-covered high hill or mountain is interposed to the link, for which typical diffraction loss models usually apply as good approximations, even disregarding the vegetation influence. Pragmatic approaches to incorporate the forest contribution, such as adding a clutter height, usually improve accuracy a little further. In this scope, this paper assesses the performance of some models based on the Uniform Theory of Diffraction (UTD) for RF path loss prediction in such ridges. Special attention goes to a hybrid model in which the forest is a uniform layer over a wedge that represents the ridge, and its influence is incorporated into the diffraction coefficient. The path loss predictions are compared with measurements from a mountainous region of the USA, and the statistical adherence of the models to the measured data is discussed. Overall, the slightly better performance of the models which incorporate the vegetation influence was confirmed, the hybrid model performing the best for frequencies below 910 MHz.

A novel approach to simulating debris flow runout via a three-dimensional CFD code: a case study of Xiaojia Gully

Extensive models used in debris flow runout simulations are two-dimensional with many limitations. Considering these limitations, a new three-dimensional computational fluid dynamics (CFD) code based on the finite difference method (FDM) was introduced to simulate debris flow runouts. The unique fractional area-volume obstacle representation (FAVOR), true-volume of fluid (Tru-VOF), and the renormalized group (RNG) model in the 3D CFD code were used to tackle mesh processing, free surface tracking, and turbulence, respectively. The RNG model has great performance in describing low-intensity flows and flows with strong shear regions. In addition, the 3D CFD modeling considers the vertical mobility of debris flow, which offers higher simulation accuracy compared to 2D approaches. Through simulating a case and a mesh size study, the accuracy of the model was validated and the optimal mesh size of Xiaojia Gully debris flow model was obtained, respectively. The affected areas, runout distances, deposition depths, and velocities of potential debris flows in Xiaojia Gully were acquired by adopting the present model. The simulation results show that debris flows with return periods of 50 years, 100 years, and 200 years will threaten the lives and safety of residents and their property in Xiaojia Gully. A sensitivity analysis was used to evaluate the influences of rheological parameters on this model, further verifying the rationality of the selected parameters. In general, the present model can scientifically and accurately simulate debris flows on irregular terrain and can be employed for similar risk management and engineering designs.

Sonic boom reflection over irregular terrain

An overview of recent studies on sonic boom reflection over irregular terrain is presented. Numerical simulations based on the two-dimensional Euler equations are performed using high-order finite-difference time-domain techniques, allowing for an accurate prediction of diffraction. Studies are done for two sonic boom waves: a conventional N-wave and a low-boom wave. First, ground elevation effects on sonic boom are examined. An academic ground profile, corresponding to a terrain depression, is considered to highlight mechanisms at play. In particular, caustics due to ground elevation variations induce another contribution at the ground level, in the form of a U-wave. Results for real ground profiles are then presented and cumulative effects, due to the succession of terrain irregularities, are shown. Second, propagation of sonic boom over an urban profile is investigated. Possible resonance effects inside street canyons are discussed. For all cases, statistics of noise metrics are examined. [This work was performed within the framework of the LabexCeLyA of the University of Lyon, within the program ‘‘Investissements d’Avenir” (ANR-10-LABX-0060/ANR-16-IDEX-0005) operated by the French National Research Agency and has received funding from the European Union's Horizon 2020 research and innovation programme (Grant Agreement No. 769896 (RUMBLE).]

Analysis of power requirement of a prototype four-wheeled electric vehicle under different off-road conditions

Different types of vehicles are used for various agricultural activities. Most agricultural vehicles have high power, which makes them inconvenient for elderly and female farmers in difficult farm conditions, such as irregular, inclined, and low-traction terrains. Therefore, the objective of this study is to evaluate the power requirement of a four-wheeled electric vehicle (4WEV) on various off-road conditions. In this study, the experiments were conducted on typical Korean farm roads by considering different slope, load, and road conditions as factors for the power requirement analysis. The torque data were obtained for 0°, 5°, 10°, and 15° slopes with 100, 300, and 500 kg payloads. The rotational speed of the wheel was constant at 50, 60, or 70 rpm for each slope and payload condition on concrete and asphalt roads. The average power required by the 4WEV was recorded to be 0.84 ± 0.025 kW and 0.85 ± 0.087 kW with 500 kg payload on 15° inclined concrete and asphalt roads, respectively. Similarly, the minimum power recorded was 0.29 ± 0.023 kW and 0.31 ± 0.069 kW with 500 kg payload at 70 rpm wheel speed on completely horizontal concrete and asphalt roads, respectively. The 60 and 50 rpm speeds showed the maximum and minimum power at 15° and 0° slopes, respectively, during the experiment. However, the maximum power requirement varies with the load condition and wheel speed under different off-road conditions. The developed 4WEV could satisfactorily scale 15° slopes with 500 kg payloads without any difficulty.

A case study of debris flow risk assessment and hazard range prediction based on a neural network algorithm and finite volume shallow water flow model

Due to the need of economic development and energy structure adjustment, China intends to build a number of pumped storage power stations for hydroelectric storage to generate electricity. Pumped storage power stations are generally built in mountainous or hilly areas where sufficient water and height differences will provide the adequate head difference. Geological processes, such as debris flows, often occur in mountainous areas and are one of the main threats to power stations and related projects. In this work, the debris flows in the engineering area of a pumped storage power station in Shangyi County, Hebei Province were selected as a case study. The neural network model was adopted to quantitatively calculate the probability of debris flows. Then, risk zoning was implemented according to the probability values. Finally, the debris flow numerical simulation software SFLOW, which is based on the finite volume shallow water flow model, was used for high-risk gullies. The spatial hazard range of each debris flow was predicted for rainfall frequencies of 20, 50, 100, and 200 years. And the sensitivity of parameters affecting debris flow migration and the advantages of SFLOW compared with FLO-2D software were discussed. In general, the SFLOW model can accurately and efficiently solve the problem of fluid flow on irregular terrain and can be applied to similar engineering projects.

Characteristic Features of Urban-Planning Solution of “Udarnik” Health Resort in Zheleznovodsk

Already during the first years of the Soviet regime the government prescribed a line of improvement concerning the state of health resort areas of the country in order to provide proper recreation to the working population. In this connection a vast building program of new health resorts, medical and recreation centers is launched in the towns of the Caucasian Mineral Waters; the development of those took into consideration two essential peculiarities of the territory – its mountain terrain and a specific structure of historic development. The case in point of such design is the building of “Udamik” health resort in Zheleznovodsk; in its urban-planning solutions the authors of the construction, I. A. Fomin and M. I. Roslavlev, managed to reflect influence of the surrounding low-rise residential development and considerable changes in elevation and irregular terrain of the plot.

Bringing Semantics to the Vineyard: An Approach on Deep Learning-Based Vine Trunk Detection

The development of robotic solutions in unstructured environments brings several challenges, mainly in developing safe and reliable navigation solutions. Agricultural environments are particularly unstructured and, therefore, challenging to the implementation of robotics. An example of this is the mountain vineyards, built-in steep slope hills, which are characterized by satellite signal blockage, terrain irregularities, harsh ground inclinations, and others. All of these factors impose the implementation of precise and reliable navigation algorithms, so that robots can operate safely. This work proposes the detection of semantic natural landmarks that are to be used in Simultaneous Localization and Mapping algorithms. Thus, Deep Learning models were trained and deployed to detect vine trunks. As significant contributions, we made available a novel vine trunk dataset, called VineSet, which was constituted by more than 9000 images and respective annotations for each trunk. VineSet was used to train state-of-the-art Single Shot Multibox Detector models. Additionally, we deployed these models in an Edge-AI fashion and achieve high frame rate execution. Finally, an assisted annotation tool was proposed to make the process of dataset building easier and improve models incrementally. The experiments show that our trained models can detect trunks with an Average Precision up to 84.16% and our assisted annotation tool facilitates the annotation process, even in other areas of agriculture, such as orchards and forests. Additional experiments were performed, where the impact of the amount of training data and the comparison between using Transfer Learning and training from scratch were evaluated. In these cases, some theoretical assumptions were verified.

Hexapod Robot Gait Switching for Energy Consumption and Cost of Transport Management Using Heuristic Algorithms

Due to the prospect of using walking robots in an impassable environment for tracked or wheeled vehicles, walking locomotion is one of the most remarkable accomplishments in robotic history. Walking robots, however, are still being deeply researched and created. Locomotion over irregular terrain and energy consumption are among the major problems. Walking robots require many actuators to cross different terrains, leading to substantial consumption of energy. A robot must be carefully designed to solve this problem, and movement parameters must be correctly chosen. We present a minimization of the hexapod robot’s energy consumption in this paper. Secondly, we investigate the reliance on power consumption in robot movement speed and gaits along with the Cost of Transport (CoT). To perform optimization of the hexapod robot energy consumption, we propose two algorithms. The heuristic algorithm performs gait switching based on the current speed of the robot to ensure minimum energy consumption. The Red Fox Optimization (RFO) algorithm performs a nature-inspired search of robot gait variable space to minimize CoT as a target function. The algorithms are tested to assess the efficiency of the hexapod robot walking through real-life experiments. We show that it is possible to save approximately 7.7–21% by choosing proper gaits at certain speeds. Finally, we demonstrate that our hexapod robot is one of the most energy-efficient hexapods by comparing the CoT values of various walking robots.

Design and Development of an Autonomous Quadruped Robot

This research paper contains the work done on the ‘Design and development of an Autonomous quadruped robot’ – a system engineered to complete tasks like carrying weaponry and materials for military applications. The primary aim of the project was to design a quadruped that works successfully in harsh conditions and irregular terrain were human intervention is impossible or hard. Initially, individual components of the design were designed and modifications were made according to the requirements. The development was carried out in five major steps including frame assignment, DH parameter analysis, Kinematic and dynamic analysis, Multibody simulation, Stability analysis and execution of gaits. The average time taken for the device to complete on cycle was found to be 10 seconds in crawl gait and around 8 seconds in trot gait. Further tests on the final device also directed a consistent results in its functionality and time taken for the quadruped to complete one gait cycle.As such, the performance of the quadruped is found to be successful and also open to further modification for better performance and varied usage requirements since the research on autonomous quadruped is at its early stages of development.

Estimation of co-channel interference between cities caused by ducting and turbulence

With the rapid development of the fifth-generation (5G) mobile communication technology, the application of each frequency band has reached the extreme, causing mutual interference between different modules. Hence, there is a requirement for detecting filtering and preventing interference. In the troposphere, over-the-horizon propagation occurs in atmospheric ducts and turbulent media. The effects of both ducting and turbulence can increase the probability of occurrence of long-distance co-channel interference (CCI), in turn, severely affecting the key performance indicators such as system access, handover and drop. In the 5G era, to ensure communication channels and information security, CCI must be reduced. This paper introduces a scattering parabolic equation algorithm for calculating signal propagation in atmospheric ducts on irregular terrain boundaries. It combines Hitney’s radio physical optical model and Wagner’s nonuniform turbulent scattering model for calculating the tropospheric scattering in an evaporation duct or a surface-based duct. The new model proposes a tropospheric scattering parabolic equation algorithm for various tropospheric duct environments. Finally, as a specific case, the topographical boundaries between several cities in the East China Plain were considered, and the over-the-horizon propagation loss was simulated for various ducting and turbulent environments. The simulation results were used to evaluate whether CCI would occur between cities in a specific environment.