scholarly journals Uji Presisi dari Nonholonomic Mobile Robot pada Rancang Bangun Sistem Navigasi

Author(s):  
Desmas A. Patriawan ◽  
Bagoes P. Natakusuma ◽  
Ahmad Anas Arifin ◽  
Hasan S. Maulana ◽  
Hery Irawan ◽  
...  

Navigasi menjadi bagian yang penting bagi kendaraan. Global positioning system (GPS) merupakan sistem navigasi yang paling banyak digunakan pada kendaraan. Namun dengan akurasi 5-10 meter membuat GPS tidak bisa diaplikasikan dalam bagian sistem kendali pada kendaraan. Penambahan sensor inertia measurement unit (IMU) diharapkan mampu menambahkan akurasi pada Gerakan kendaraan. Kendaran yang digunakan adalah robot beroda dengan sistem nonholonomic. Pada robot ini dipasang Sensor IMU, GPS dan kontroler supaya robot tersebut bisa berputar lalu melaju secara lurus dengan kordinat yang sudah ditentukan. Hasil pengujian didapatkan robot memiliki respon time sebesar 4.1 detik tanpa kontroler dan 2.1 detik dengan kontroler. Akurasi sudut dari 5  menjadi 2 .

2019 ◽  
Vol 9 (6) ◽  
pp. 1165
Author(s):  
Hong’an Yang ◽  
Xuefeng Bao ◽  
Shaohua Zhang ◽  
Xu Wang

Aimed at the problem that experimental verifications are difficult to execute due to lacking effective experimental platforms in the research field of multi-robot formation, we design a simple multi-robot formation platform. This proposed general and low-cost multi-robot formation platform includes the indoor global-positioning system, the multi-robot communication system, and the wheeled mobile robot hardware. For each wheeled mobile robot in our platform, its real-time position information in the centimeter‑level precise is obtained by the Marvelmind Indoor Navigation System and orientation information is obtained by the six-degree-of-freedom gyroscope. The Transmission Control Protocol/Internet Protocol (TCP/IP) wireless communication infrastructure is selected to support the communication among robots and the data collection in the process of experiments. Finally, a set of leader–follower formation experiments are performed by our platform, which include three trajectory tracking experiments of different types and numbers under deterministic environment and a formation-maintaining experiment with external disturbances. The results illustrate that our multi-robot formation platform can be effectively used as a general testbed to evaluate and verify the feasibility and correctness of the theoretical methods in the multi-robot formation. What is more, the proposed simple and general formation platform is beneficial to the development of platforms in the fields of multi-robot coordination, formation control, and search and rescue missions.


Author(s):  
John J. Hall ◽  
Robert L. Williams ◽  
Frank van Graas

Abstract The Department of Mechanical Engineering and the Avionics Engineering Center at Ohio University are developing an electromechanical system for the calibration of an inertial measurement unit (IMU) using global positioning system (GPS) antennas. The GPS antennas and IMU are mounted to a common platform to be oriented in the angular roll, pitch, and yaw motions. Vertical motion is also included to test the systems in a vibrational manner. A four-dof system based on the parallel Carpal Wrist is under development for this task. High-accuracy positioning is not required from the platform since the GPS technology provides absolute positioning for the IMU calibration process.


2009 ◽  
Vol 26 (6-7) ◽  
pp. 537-548 ◽  
Author(s):  
Yoshisada Nagasaka ◽  
Hidefumi Saito ◽  
Katsuhiko Tamaki ◽  
Masahiro Seki ◽  
Kyo Kobayashi ◽  
...  

2018 ◽  
Vol 14 (11) ◽  
pp. 155014771881257
Author(s):  
ChoonSung Nam ◽  
Dong-Ryeol Shin

Information communication technology related vehicle services need to support location and the transmission of communication and traffic information between vehicles, or between vehicles and infrastructure. In particular, the technology for the measurement of the accurate location of a vehicle is dependent on location-determination technology like Global Positioning System, and this technology is very important for vehicle driving and location services. If, however, a vehicle is in a Global Positioning System radio-shadow area, neither a Global Positioning System nor a Differential Global Positioning System can accurately measure the corresponding location because of a high error rate caused by the shadowing intervention. Even an Inertial Measurement Unit could provide inaccurate location data due to sensor drift faults around corners and traffic-road speed dumps. Vehicles, therefore, need an absolute location to prevent the provision of inaccurate vehicle-location data that is due to radio-shadow areas and relational Inertial Measurement Unit positions. To achieve this, we assume that vehicle-to-infrastructure communication is possible between a vehicle and roadside unit in Vehicular Ad hoc Networks. We used iBeacon at the roadside unit and revised its Universally Unique Identifier so that it generates absolute Global Positioning System location data; that is, moving vehicles can receive absolute Global Positioning System data from the roadside unit-based iBeacon. We compared the proposed method with current Global Positioning System and Inertial Measurement Unit systems for the following two cases: one with a radio-shadow area and one without. We proved that the proposed method generates location data that are more accurate than those of the other methods.


Sensors ◽  
2021 ◽  
Vol 21 (17) ◽  
pp. 5695
Author(s):  
Hadi Nobari ◽  
Norbert Keshish Banoocy ◽  
Rafael Oliveira ◽  
Jorge Pérez-Gómez

The aim of the study was to determine the between-match and between-halves match variability of various Global Positioning System (GPS) variables and metabolic power average (MPA) in competitions, based on the match results obtained by professional soccer players over a full season. Observations on individual match performance measures were undertaken on thirteen outfield players competing in the Iranian Premier League. The measures selected for analysis included total duration, accelerations in zones (AccZ1, 2, and 3), decelerations in zones (DecZ1, 2, and 3), and MPA collected by the Wearable Inertial Measurement Unit (WIMU). The GPS manufacturer set the thresholds for the variables analyzed as follows: AccZ1 (<2 m.s−2); AccZ2 (2 to 4 m.s−2); AccZ3 (>4 m.s−2); DecZ1 (<−2 m.s−2); DecZ2 (−2 to −4 m.s−2); DecZ3 (>−4 m.s−2). The results revealed significant differences between wins and draws for the duration of the match and draws compared to wins for the first- half duration (p ≤ 0.05; ES = 0.36 [−0.43,1.12]), (p ≤ 0.05; ES = −7.0 [−8.78, −4.78], respectively. There were significant differences on AccZ1 during the first-half between draws and defeats (p ≤ 0.05; ES = −0.43 [−1.32,0.46]), for AccZ3 in the second-half between draws and defeats (p ≤ 0.05; ES = 1.37 [0.48,2.25]). In addition, there were significant differences between wins and draws (p ≤ 0.05; ES = 0.22 [−0.62,1.10]), and wins and defeats for MPA in the first- half (p ≤ 0.05; ES = 0.34 [−0.65,1.22]). MPA showed further differences between draws and defeats in the second- half (p ≤ 0.05; ES = 0.57 [−0.22,1.35]). Descriptive analysis revealed differences between the first and second half for wins in AccZ2 (p = 0.005), DecZ2 (p = 0.029), and MPA (p = 0.048). In addition, draws showed significant differences between the first and second half in duration, AccZ1, AccZ2, and DecZ2 (p = 0.008), (p = 0.017), (p = 0.040), and (p = 0.037) respectively. Defeats showed differences between the first and second half in AccZ1, AccZ3, and MPA (p = 0.001), (p = 0.018), and (p = 0.003) respectively. In summary, the study reveals large variations between the match duration, accelerometer variables, and MPA both within and between matches. Regardless of the match outcome, the first half seems to produce greater outputs. The results should be considered when performing a half-time re-warm-up, as this may be an additional factor influencing the drop in the intensity markers in the second half in conjunction with factors such as fatigue, pacing strategies, and other contextual variables that may influence the results.


Author(s):  
Jaganathan Ranganathan ◽  
William H. Semke

An active three-axis gimbal system is developed to allow small fixed wing Unmanned Aircraft Systems (UAS) platforms to estimate accurate position information by pointing at a target and also to track a known target location. Specific targets vary from a stationary point on the ground to aircraft in the national airspace. The payload developed to accomplish this at the University of North Dakota is the Surveillance by University of North Dakota Observational Gimbal (SUNDOG). This paper will focus on a novel, nonlinear closed form analytical algorithm developed to calculate the exact rotation angles for a three-axis gimbal system to point a digital imaging sensor at a target, as well as how to estimate accurate position of a target by using the pointing angles of a three-axis gimbal system. A kinematic analysis is done on a three-axis gimbal system to get the appropriate model of gimbal rotations in order to point at a certain location on the ground. The mathematical model includes an inertial coordinate system that has coordinates fixed to the Earth, a coordinate system that is body-fixed to the aircraft, and a third coordinate system that is fixed to the gimbal. Therefore, multiple three-dimensional transformations are required to accurately provide the necessary pointing angles to the gimbal system. The autonomous control system uses Global Positioning System (GPS), Inertial Measurement Unit (IMU), and other sensor data to estimate position and attitude during flight. Since the algorithm is entirely based on Inertial Measurement Unit (IMU) and Global Positioning System (GPS) device inputs, any error from these devices cause offset in the target location. Hence, an error analysis is carried out to find the offset distance and the operating range of the algorithm. The main advantage obtained in the three-axis gimbal system is that the orientation of the image will always be aligned in a specified direction for effective interpretation. The closed form expressions to the non-linear transformations provide simple solutions easily programmed without large computational expense. Experimental work will be carried out in a controlled environment and in flight testing to show the autonomous tracking ability of the gimbal system. Simulation and experimental data illustrating the effectiveness of the surveillance algorithms is presented.


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