scholarly journals The Autonomous Pinger Unit of the Acoustic Navigation Network in EnEx-RANGE: an autonomous in-ice melting probe with acoustic instrumentation

2020 ◽  
pp. 1-10
Author(s):  
Lars Steffen Weinstock ◽  
Simon Zierke ◽  
Dmitry Eliseev ◽  
Peter Linder ◽  
Cornelius Vollbrecht ◽  
...  
Keyword(s):  
Internal State ◽  
Field Tests ◽  
Space Mission ◽  
Position Estimation ◽  
Guidance System ◽  
Point Of Interest ◽  
Spatially Distributed ◽  
Acoustic Navigation ◽  
On Chip ◽  
Performance Results

Abstract The Autonomous Pinger Unit (APU) is an electro-thermal drill with acoustic instrumentation developed for the project EnEx-RANGE in view of a future space mission for the sub-surface exploration of Saturn's moon Enceladus. A main goal is the development of navigation technology for an acoustic guidance system allowing maneuvering a probe through glacial ice. In total 13 APUs were built and tested in terrestrial analog scenarios on alpine glaciers. The APUs form a spatially distributed network that defines a system of reference for the navigation of the maneuverable probe to a point of interest. The APUs have a novel melting head, slow control systems, and a modern system-on-chip (SoC) module that controls the probe and processes the recorded data. The APUs use acoustic emitters and receivers to measure the transit time of acoustic signals between them, allowing for the position reconstruction of all APUs by trilateration. Several auxiliary sensors monitor the internal state of the probe and assist the position estimation. With this instrumentation, the APUs have the ability of dynamically optimizing themselves within the network by changing their position. This paper gives an overview of the developed APU hardware and presents performance results from the field tests.

From Science to Practice: Improving ROP by Utilizing a Cloud-Based Machine-Learning Solution in Real-Time Drilling Operations

2021 ◽  
Author(s):  
Kriti Singh ◽  
Sai Yalamarty ◽  
Curtis Cheatham ◽  
Khoa Tran ◽  
Greg McDonald
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Situational Awareness ◽  
Field Tests ◽  
Field Trials ◽  
Permian Basin ◽  
Lateral Vibrations ◽  
Drilling Parameters ◽  
Drilling Conditions ◽  
Performance Results

Abstract This paper is a follow up to the URTeC (2019-343) publication where the training of a Machine Learning (ML) model to predict rate of penetration (ROP) is described. The ML model gathers recent drilling parameters and approximates drilling conditions downhole to predict ROP. In real time, the model is run through an optimization sweep by adjusting parameters which can be controlled by the driller. The optimal drilling parameters and modeled ROP are then displayed for the driller to utilize. The ML model was successfully deployed and tested in real time in collaboration with leading shale operators in the Permian Basin. The testing phase was split in two parts, preliminary field tests and trials of the end-product. The key learnings from preliminary field tests were used to develop an integrated driller's dashboard with optimal drilling parameters recommendations and situational awareness tools for high dysfunction and procedural compliance which was used for designed trials. The results of field trials are discussed where subject well ROP was improved between 19-33% when comparing against observation/control footage. The overall ROP on subject wells was also compared against offset wells with similar target formations, BHAs, and wellbore trajectories. In those comparisons against qualified offsets, ROP was improved by as little as 5% and as much as 33%. In addition to comparing ROP performance, results from post-run data analysis are also presented. Detailed drilling data analytics were performed to check if using the recommendations during the trial caused any detrimental effects such as divergence in directional trends or high lateral or axial vibrations. The results from this analysis indicate that the measured downhole axial and lateral vibrations were in the safe zone. Also, no significant deviations in rotary trends were observed.

Decentralized Control for Swarm Robots That Can Effectively Execute Spatially Distributed Tasks

2020 ◽  
Vol 26 (2) ◽  
pp. 242-259 ◽  
Author(s):  
Takeshi Kano ◽  
Eiichi Naito ◽  
Takenobu Aoshima ◽  
Akio Ishiguro
Keyword(s):  
Decentralized Control ◽  
Internal State ◽  
Search And Rescue ◽  
Multiple Robots ◽  
Rescue Operation ◽  
Control Scheme ◽  
Swarm Robots ◽  
Multiple Tasks ◽  
Spatially Distributed ◽  
Distributed Tasks

A swarm robotic system is a system in which multiple robots cooperate to fulfill a macroscopic function. Many swarm robots have been developed for various purposes. This study aims to design swarm robots capable of executing spatially distributed tasks effectively, which can be potentially used for tasks such as search-and-rescue operation and gathering scattered garbage in rooms. We propose a simple decentralized control scheme for swarm robots by extending our previously proposed non-reciprocal-interaction-based model. Each robot has an internal state, called its workload. Each robot first moves randomly to find a task, and when it does, its workload increases, and then it attracts its neighboring robots to ask for their help. We demonstrate, via simulations, that the proposed control scheme enables the robots to effectively execute multiple tasks in parallel under various environments. Fault tolerance of the proposed system is also demonstrated.

scholarly journals Indoor Localization System Based on Bluetooth Low Energy for Museum Applications

Electronics ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 1055 ◽  
Author(s):  
Romeo Giuliano ◽  
Gian Carlo Cardarilli ◽  
Carlo Cesarini ◽  
Luca Di Nunzio ◽  
Francesca Fallucchi ◽  
...  
Keyword(s):  
Indoor Localization ◽  
Position Estimation ◽  
Low Energy ◽  
Least Square ◽  
Feed Forward Neural Network ◽  
Position Information ◽  
Bluetooth Low Energy ◽  
Performance Results ◽  
Linear Least Square ◽  
Position Estimate

In the last few years, indoor localization has attracted researchers and commercial developers. Indeed, the availability of systems, techniques and algorithms for localization allows the improvement of existing communication applications and services by adding position information. Some examples can be found in the managing of people and/or robots for internal logistics in very large warehouses (e.g., Amazon warehouses, etc.). In this paper, we study and develop a system allowing the accurate indoor localization of people visiting a museum or any other cultural institution. We assume visitors are equipped with a Bluetooth Low Energy (BLE) device (commonly found in modern smartphones or in a small chipset), periodically transmitting packets, which are received by geolocalized BLE receivers inside the museum area. Collected packets are provided to the locator server to estimate the positions of the visitors inside the museum. The position estimation is based on a feed-forward neural network trained by a measurement campaign in the considered environment and on a non-linear least square algorithm. We also provide a strategy for deploying the BLE receivers in a given area. The performance results obtained from measurements show an achievable position estimate accuracy below 1 m.

Traction Performance of Transit and Paratransit Vehicles in Winter

2000 ◽  
Vol 1731 (1) ◽  
pp. 40-50 ◽  
Author(s):  
Lutfi Raad ◽  
Jian John Lu
Keyword(s):  
Public Transportation ◽  
Field Tests ◽  
Emergency Situation ◽  
Hill Climbing ◽  
Stopping Distance ◽  
Vehicle Type ◽  
Research Findings ◽  
Public Transportation System ◽  
Performance Results ◽  
Transit Bus

The traction performance of transit and paratransit vehicles during the winter is an important factor in public transportation system operations. Vehicle traction forces are significantly reduced on snowy or icy surfaces, specifically during stopping, starting, cornering, and hill climbing. Reduced traction increases stopping distances and decreases controllability when a vehicle stops in an emergency situation. This study evaluated the traction performance of transit and paratransit vehicles on snowy and icy surfaces. Field tests were conducted in Fairbanks, Alaska, using three types of vehicles—a 41-passenger transit bus, a 32-passenger transit bus, and a 9-passenger paratransit vehicle. Each vehicle was tested for different combinations of tire types, including highway tires, snow tires, studded-siped tires, highway three-rib tires, all-season tires, and snow-siped tires. Tests of winter traction performance evaluated stopping distance, starting traction, hill climbing, cornering, and controllability. For similar tire combinations and surface conditions, the tested transit and paratransit vehicles had different traction performance. Results indicate that winter traction performance is significantly influenced by vehicle type, tire combination, and road surface (compacted snow or ice). Research findings and recommendations for tire combinations best suited for winter traction are presented.

scholarly journals The TaPaSCo Open-Source Toolflow

2021 ◽  
Author(s):  
Carsten Heinz ◽  
Jaco Hofmann ◽  
Jens Korinth ◽  
Lukas Sommer ◽  
Lukas Weber ◽  
...  
Keyword(s):  
Open Source ◽  
System Integration ◽  
Design Space Exploration ◽  
Systems On Chip ◽  
Spatially Distributed ◽  
On Chip ◽  
Many Core ◽  
Hardware Designs ◽  
Application Specific

AbstractThe integration of FPGA-based accelerators into a complete heterogeneous system is a challenging task faced by many researchers and engineers, especially now that FPGAs enjoy increasing popularity as implementation platforms for efficient, application-specific accelerators for domains such as signal processing, machine learning and intelligent storage. To lighten the burden of system integration from the developers of accelerators, the open-source TaPaSCo framework presented in this work provides an automated toolflow for the construction of heterogeneous many-core architectures from custom processing elements, and a simple, uniform programming interface to utilize spatially distributed, parallel computation on FPGAs. TaPaSCo aims to increase the scalability and portability of FPGA designs through automated design space exploration, greatly simplifying the scaling of hardware designs and facilitating iterative growth and portability across FPGA devices and families. This work describes TaPaSCo with its primary design abstractions and shows how TaPaSCo addresses portability and extensibility of FPGA hardware designs for systems-on-chip. A study of successful projects using TaPaSCo shows its versatility and can serve as inspiration and reference for future users, with more details on the usage of TaPaSCo presented in an in-depth case study and a short overview of the workflow.

scholarly journals Obstacle Tracking on Unmanned Surface Vehicle Using Kalman Filter

2021 ◽  
Vol 5 (2) ◽  
Author(s):  
Rusdhianto Effendi Abdul Kadir ◽  
Mochammad Sahal ◽  
Yusuf Bilfaqih ◽  
Zulkifli Hidayat ◽  
Gaung Jagad
Keyword(s):  
Kalman Filter ◽  
System Design ◽  
Relative Position ◽  
Water Surface ◽  
Tracking System ◽  
Position Estimation ◽  
Guidance System ◽  
Light Detection And Ranging ◽  
Unmanned Surface Vehicle ◽  
Surrounding Environment

Unmanned Surface Vehicles (USV) are self-driving vehicles that operate on the water surface. In order to be operated autonomously, USV has a guidance system designed for path planning to reach its destination. The ability to detect obstacles in its paths is one of the important factors to plan a new path in order to avoid obstacles and reach its destination optimally. This research designed an obstacle tracking system which integrates USV perception sensors such as camera and Light Detection and Ranging (LiDaR) to gain information of the obstacle’s relative position in the surrounding environment to the ship. To improve the relative position estimation of the obstacles to the ship, Kalman filter is applied to reduce the measurements noises. The results of the system design are simulated using MATLAB software so that results can be analyzed to see the performance of the system design. Results obtained using the Kalman filter show 12% noise reduction. Keywords: filter kalman, obstacle tracking, unmanned surface vehicle.

Motion Restricted Information Filter for Indoor Bluetooth Positioning

2012 ◽  
Vol 3 (3) ◽  
pp. 54-66 ◽  
Author(s):  
Liang Chen ◽  
Heidi Kuusniemi ◽  
Yuwei Chen ◽  
Ling Pei ◽  
Tuomo Kröger ◽  
...  
Keyword(s):  
Prior Information ◽  
Information Filtering ◽  
Field Tests ◽  
Signal Strength ◽  
Position Estimation ◽  
Indoor Navigation ◽  
Positioning Accuracy ◽  
Information Filter ◽  
Positioning Method ◽  
Wireless Positioning

This paper studies wireless positioning using a network of Bluetooth signals. Fingerprints of received signal strength indicators (RSSI) are used for localization. Due to the relatively long interval between the available consecutive Bluetooth signal strength measurements, the authors propose a method of information filtering with speed detection, which combines the estimation information from the RSSI measurements with the prior information from the motion model. Speed detection is further assisted to correct the outliers of position estimation. The field tests show that the new algorithm proposed applying information filter with speed detection improves the horizontal positioning accuracy of indoor navigation with about 17% compared to the static fingerprinting positioning method, achieving a 4.2 m positioning accuracy on the average, and about 16% improvement compared to the point Kalman filter.

scholarly journals UWB-Based Self-Localization Strategies: A Novel ICP-Based Method and a Comparative Assessment for Noisy-Ranges-Prone Environments

Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5613
Author(s):  
Francisco Bonnin-Pascual ◽  
Alberto Ortiz
Keyword(s):  
Real Option ◽  
Signal Transmission ◽  
Wide Band ◽  
Position Estimation ◽  
Metallic Structures ◽  
Positioning Systems ◽  
Estimation Algorithms ◽  
Novel Method ◽  
Generic Agents ◽  
Performance Results

Ultra-Wide-Band (UWB) positioning systems are now a real option to estimate the position of generic agents (e.g., robots) within indoor/GPS-denied environments. However, these environments can comprise metallic structures or other elements which can negatively affect the signal transmission and hence the accuracy of UWB-based position estimations. Regarding this fact, this paper proposes a novel method based on point-to-sphere ICP (Iterative Closest Point) to determine the 3D position of a UWB tag. In order to improve the results in noise-prone environments, our method first selects the anchors’ subset which provides the position estimate with least uncertainty (i.e., largest agreement) in our approach. Furthermore, we propose a previous stage to filter the anchor-tag distances used as input of the ICP stage. We also consider the addition of a final step based on non-linear Kalman Filtering to improve the position estimates. Performance results for several configurations of our approach are reported in the experimental results section, including a comparison with the performance of other position-estimation algorithms based on trilateration. The experimental evaluation under laboratory conditions and inside the cargo hold of a vessel (i.e., a noise-prone scenario) proves the good performance of the ICP-based algorithm, as well as the effects induced by the prior and posterior filtering stages.

scholarly journals Design and Experimentation of an Aerial Seeding System for Rapeseed Based on an Air-Assisted Centralized Metering Device and a Multi-Rotor Crop Protection UAV

2020 ◽  
Vol 10 (24) ◽  
pp. 8854
Author(s):  
Xiaomao Huang ◽  
Shun Zhang ◽  
Chengming Luo ◽  
Wencheng Li ◽  
Yitao Liao
Keyword(s):  
Orthogonal Experiment ◽  
Crop Protection ◽  
Field Tests ◽  
Economic Benefits ◽  
Variation Coefficient ◽  
Seeding Rate ◽  
Rapeseed Production ◽  
The Stability ◽  
Performance Results ◽  
Aerial Seeding

To improve the overall mechanization level of rapeseed production in China, especially in some hilly regions where ground machinery cannot enter the fields or can only enter with very low economic benefits, a special aerial seeding system for rapeseed based on a miniature air-assisted centralized metering device was designed and tested in this study. Unlike existing commercial aerial seeding systems, the proposed seed meter was a miniaturized version derived from the traditional air-feeding seed meter on ground planters. The new version contained a redesigned seed feeding component to overcome problems of serious air backflow to the seed box and difficult seed feeding after miniaturization. Three groups of experiments were designed and conducted to optimize the parameters of the seed meter and test its performance. Results from the orthogonal experiment showed that the seed feeding component performed best when the seed layer thickness was 45 mm, the rotational speed of the gear disc was 45 r/min, and the airflow pressure was 2450 Pa. Results from the static workbench test showed that the designed seeding system had a maximum average total sowing efficiency of 537.17 g/min, with the maximum values of the stability variation coefficient of total seeding rate (seven ports) and the consistency variation coefficient between each port was 2.37% and 4.89%, respectively. Field tests further proved that the designed aerial seeding system could work stably, uniformly, and efficiently, so that the agronomic requirements of rape crop planting could be well met.

CFD, Thermal and Stress Analysis for daVinci X-Prize Manned Space Mission: Part 2 (Keynote)

2004 ◽  
Author(s):  
Vladimir Kudriavtsev ◽  
Brian Feeney ◽  
Ta-Liang Hsu ◽  
Alexei Borovkov ◽  
Kalman Rooz ◽  
...  
Keyword(s):  
Stress Analysis ◽  
Da Vinci ◽  
Low Cost ◽  
Internal Heat ◽  
Space Mission ◽  
Guidance System ◽  
Full Account ◽  
Engineering Research ◽  
Wide Range ◽  
Prize Competition

In the present article we review engineering and research efforts conducted by a group of volunteers with the help of advanced engineering commercial software (CFD-ACE+, ANSYS, CFD-FASTRAN, Matlab/Simulink, Autodesk Inventor, Maple) in support of the da Vinci Project, the first Canadian competitor in the International X Prize Competition. Full account of these activities was presented at the da Vinci Space Project Technical Conference Program [1]. Announced in 1996 to promote the development and flight of spacecraft for low-cost commercial transport of humans into space, the international X-Prize Foundation is providing a purse of US$10 million to the first competitor who can safely launch and land a manned spacecraft to an altitude of 100 kilometers (the international border of space), twice in a two-week period. The first Canadian entry in this competition, the fully volunteer da Vinci Project (a wholly owned by ORVA Space Corp.) has put years of engineering research, design and developmental testing into the vehicle design, propulsion and flight guidance system. A full-scale flight-engineering prototype of the manned rocket has been constructed. Detailed engineering and fabrication of the full-scaled manned rocket named Wild Fire Mk VI is currently underway. Flight-testing of the manned rocket and X-Prize competition flights are targeted to continue throughout 2004. For R&D efforts on the project, a wide range of engineering software was utilized for CAD, basic engineering calculations, trajectory analysis, dynamics and mission control, supersonic external aerodynamics, and internal heat flow. Part 1 of this lecture appearing in Volume 1 describes space mission, thermal and CFD analyses and CAD integration. This installment describes how ANSYS and LSDYNA software packages were utilized to perform stress analysis of the space capsule and the rocket block.

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