scholarly journals Altitude Measurement-Based Optimization of the Landing Process of UAVs

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1151
Author(s):  
Dariusz Horla ◽  
Wojciech Giernacki ◽  
Jacek Cieślak ◽  
Pascual Campoy
Keyword(s):  
Motion Capture ◽  
Minimum Energy ◽  
Minimum Time ◽  
Motion Capture System ◽  
Control Loop ◽  
Performance Indices ◽  
Novel Approach ◽  
Aerial Vehicle ◽  
Altitude Control ◽  
Flying Robot

The paper addresses the loop shaping problem in the altitude control of an unmanned aerial vehicle to land the flying robot with a specific landing scenario adopted. The proposed solution is optimal, in the sense of the selected performance indices, namely minimum-time, minimum-energy, and velocity-penalized related functions, achieving their minimal values, with numerous experiments conducted throughout the development and preparation to the Mohamed Bin Zayed International Robotics Challenge (MBZIRC 2020). A novel approach to generation of a reference altitude trajectory is presented, which is then tracked in a standard, though optimized, control loop. Three landing scenarios are considered, namely: minimum-time, minimum-energy, and velocity-penalized landing scenarios. The experimental results obtained with the use of the Simulink Support Package for Parrot Minidrones, and the OptiTrack motion capture system proved the effectiveness of the proposed approach.

scholarly journals Functional cortical localization of the tongue using corticokinematic coherence with a deep learning-assisted motion capture system

2021 ◽  
Author(s):  
Hitoshi Maezawa ◽  
Momoka Fujimoto ◽  
Yutaka Hata ◽  
Masao Matsuhashi ◽  
Hiroaki Hashimoto ◽  
...  
Keyword(s):  
Deep Learning ◽  
Motion Capture ◽  
Video Camera ◽  
Motion Capture System ◽  
Control Task ◽  
Novel Approach ◽  
Functional Localization ◽  
Movement Frequency ◽  
Tongue Movements ◽  
The Right

Measuring the corticokinematic coherence (CKC) between magnetoencephalographic and movement signals using an accelerometer can evaluate the functional localization of the primary sensorimotor cortex (SM1) of the upper limbs. However, it is difficult to determine the tongue CKC because an accelerometer yields excessive magnetic artifacts. We introduce and validate a novel approach for measuring the tongue CKC using a deep learning-assisted motion capture system with videography, and compare it with an accelerometer in a control task measuring finger movement. Twelve healthy volunteers performed rhythmical side-to-side tongue movements in the whole-head magnetoencephalographic system, which were simultaneously recorded using a video camera and examined offline using a deep learning-assisted motion capture system. In the control task, right finger CKC measurements were simultaneously evaluated via motion capture and an accelerometer. The right finger CKC with motion capture was significant at the movement frequency peaks or its harmonics over the contralateral hemisphere; the motion-captured CKC was 84.9% similar to that with the accelerometer. The tongue CKC was significant at the movement frequency peaks or its harmonics over both hemispheres, with no difference between the left and right hemispheres. The CKC sources of the tongue were considerably lateral and inferior to those of the finger. Thus, the CKC based on deep learning-assisted motion capture can evaluate the functional localization of the tongue SM1. In this approach, because no devices are placed on the tongue, magnetic noise, disturbances due to tongue movements, risk of aspiration of the device, and risk of infection to the experimenter are eliminated.

scholarly journals Functional cortical localization of tongue movements using corticokinematic coherence with a deep learning-assisted motion capture system

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Hitoshi Maezawa ◽  
Momoka Fujimoto ◽  
Yutaka Hata ◽  
Masao Matsuhashi ◽  
Hiroaki Hashimoto ◽  
...  
Keyword(s):  
Deep Learning ◽  
Motion Capture ◽  
Video Camera ◽  
Motion Capture System ◽  
Control Task ◽  
Novel Approach ◽  
Functional Localization ◽  
Movement Frequency ◽  
Tongue Movements ◽  
The Right

AbstractCorticokinematic coherence (CKC) between magnetoencephalographic and movement signals using an accelerometer is useful for the functional localization of the primary sensorimotor cortex (SM1). However, it is difficult to determine the tongue CKC because an accelerometer yields excessive magnetic artifacts. Here, we introduce a novel approach for measuring the tongue CKC using a deep learning-assisted motion capture system with videography, and compare it with an accelerometer in a control task measuring finger movement. Twelve healthy volunteers performed rhythmical side-to-side tongue movements in the whole-head magnetoencephalographic system, which were simultaneously recorded using a video camera and examined using a deep learning-assisted motion capture system. In the control task, right finger CKC measurements were simultaneously evaluated via motion capture and an accelerometer. The right finger CKC with motion capture was significant at the movement frequency peaks or its harmonics over the contralateral hemisphere; the motion-captured CKC was 84.9% similar to that with the accelerometer. The tongue CKC was significant at the movement frequency peaks or its harmonics over both hemispheres. The CKC sources of the tongue were considerably lateral and inferior to those of the finger. Thus, the CKC with deep learning-assisted motion capture can evaluate the functional localization of the tongue SM1.

scholarly journals A Novel Approach in Low-cost Motion Capture System using Color Descriptor and Stereo Webcam

2019 ◽  
Vol 10 (5) ◽  
pp. 942
Author(s):  
Muhammad Imanullah ◽  
Eko Mulyanto Yuniarno ◽  
Adri Gabriel Sooai
Keyword(s):  
Motion Capture ◽  
Low Cost ◽  
Motion Capture System ◽  
Novel Approach ◽  
Color Descriptor

Gender differences in the Achilles tendon load during the fencing lunge

2014 ◽  
Vol 6 (3) ◽  
Author(s):  
Jonathan Kenneth Sinclair ◽  
Lindsay Bottoms
Keyword(s):  
Gender Differences ◽  
Achilles Tendon ◽  
Motion Capture ◽  
Tendon Injury ◽  
Force Platform ◽  
Motion Capture System ◽  
3D Motion ◽  
Loading Rates ◽  
Tendon Pathology ◽  
3D Motion Capture

AbstractRecent epidemiological analyses in fencing have shown that injuries and pain linked specifically to fencing training/competition were evident in 92.8% of fencers. Specifically the prevalence of Achilles tendon pathology has increased substantially in recent years, and males have been identified as being at greater risk of Achilles tendon injury compared to their female counterparts. This study aimed to examine gender differences in Achilles tendon loading during the fencing lunge.Achilles tendon load was obtained from eight male and eight female club level epee fencers using a 3D motion capture system and force platform information as they completed simulated lunges. Independent t-tests were performed on the data to determine whether differences existed.The results show that males were associated with significantly greater Achilles tendon loading rates in comparison to females.This suggests that male fencers may be at greater risk from Achilles tendon pathology as a function of fencing training/ competition.

Magnetic motion capture system using LC resonant magnetic marker composed of Ni–Zn ferrite core

2006 ◽  
Vol 99 (8) ◽  
pp. 08B312 ◽  
Author(s):  
S. Hashi ◽  
M. Toyoda ◽  
M. Ohya ◽  
Y. Okazaki ◽  
S. Yabukami ◽  
...  
Keyword(s):  
Motion Capture ◽  
Motion Capture System ◽  
Ferrite Core ◽  
Zn Ferrite ◽  
Magnetic Marker

scholarly journals Modeling and evaluating beat gestures for social robots

2021 ◽  
Author(s):  
Unai Zabala ◽  
Igor Rodriguez ◽  
José María Martínez-Otzeta ◽  
Elena Lazkano
Keyword(s):  
Motion Capture ◽  
Motion Capture System ◽  
Generative Adversarial Network ◽  
Adversarial Network ◽  
Desirable Feature ◽  
Quantitative Results ◽  
Path Lengths ◽  
End Effectors ◽  
The One ◽  
Made In

AbstractNatural gestures are a desirable feature for a humanoid robot, as they are presumed to elicit a more comfortable interaction in people. With this aim in mind, we present in this paper a system to develop a natural talking gesture generation behavior. A Generative Adversarial Network (GAN) produces novel beat gestures from the data captured from recordings of human talking. The data is obtained without the need for any kind of wearable, as a motion capture system properly estimates the position of the limbs/joints involved in human expressive talking behavior. After testing in a Pepper robot, it is shown that the system is able to generate natural gestures during large talking periods without becoming repetitive. This approach is computationally more demanding than previous work, therefore a comparison is made in order to evaluate the improvements. This comparison is made by calculating some common measures about the end effectors’ trajectories (jerk and path lengths) and complemented by the Fréchet Gesture Distance (FGD) that aims to measure the fidelity of the generated gestures with respect to the provided ones. Results show that the described system is able to learn natural gestures just by observation and improves the one developed with a simpler motion capture system. The quantitative results are sustained by questionnaire based human evaluation.

Assessing the Ergonomic Benefits of a New Adjustable Forklift Backrest

2020 ◽  
Vol 64 (1) ◽  
pp. 976-980
Author(s):  
Pranav Madhav Kuber ◽  
Ehsan Rashedi
Keyword(s):  
Comparative Study ◽  
Motion Capture ◽  
Center Of Pressure ◽  
Body Movement ◽  
Pressure Change ◽  
Motion Capture System ◽  
Design Features ◽  
Wide Range ◽  
Body Sizes ◽  
The Mean

A new forklift backrest has been developed by incorporating adjustability concepts into the design to facilitate comfort to a wide range of users. We have conducted a comparative study between the new and original backrests to assess the effectiveness of design features. Using the phenomenon of restlessness, discomfort of the user was associated with the amount of body movement, where we have used a motion- capture system and a force platform to quantify the individuals’ movement for a wide range of body sizes. Meanwhile, subjective comfort and design feedback were collected using a questionnaire. Our results showed a reduction in the mean torso movement and the maximum center of pressure change of location by 300 and 6 mm, respectively, for the new design. Taking advantage of adjustability feature, the new backrest design exhibited enhanced comfort for longer durations and reduced magnitude of discomfort for a wide range of participants’ body sizes.

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