A Robust Real-Time Control Algorithm for Whole-Body Running

2011 ◽  
Author(s):  
Xianlian Zhou ◽  
Andrzej Przekwas
Keyword(s):  
Computer Animation ◽  
High Mobility ◽  
Human Movement ◽  
Human Motion ◽  
Whole Body ◽  
Real Time Control ◽  
Dynamic Simulations ◽  
Time Control ◽  
Military Applications ◽  
Experimental Approaches

Dynamic simulations of human movement are becoming increasingly important in biomechanics, computer animation, clinical and military applications. It complements experimental approaches by providing capabilities not generally offered by the experimental approaches. Nonetheless, the dynamic simulation of human movement remains one of great challenges in biomechanics due to the high-mobility of the human body and the redundancy of body control. Over past decades, various methods have been developed to simulate human motion.

scholarly journals Compliant Humanoids Moving Toward Rehabilitation Applications: Transparent Integration of Real-Time Control, Whole-Body Motion Generation, and Virtual Reality

2019 ◽  
Vol 26 (4) ◽  
pp. 83-93
Author(s):  
Pouya Mohammadi ◽  
Enrico Mingo Hoffman ◽  
Niels Dehio ◽  
Milad S. Malekzadeh ◽  
Martin Giese ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Real Time ◽  
Body Motion ◽  
Whole Body ◽  
Motion Generation ◽  
Real Time Control ◽  
Time Control

scholarly journals Interactive Audio Augmented Reality in Participatory Performance

2021 ◽  
Vol 1 ◽  
Author(s):  
Anna N. Nagele ◽  
Valentin Bauer ◽  
Patrick G. T. Healey ◽  
Joshua D. Reiss ◽  
Henry Cooke ◽  
...  
Keyword(s):  
Augmented Reality ◽  
Human Interaction ◽  
Whole Body ◽  
Spatial Audio ◽  
Real Time Control ◽  
Performance Practices ◽  
Time Control ◽  
Audio Augmented Reality ◽  
And Performance ◽  
Participatory Performance

Interactive Audio Augmented Reality (AAR) facilitates collaborative storytelling and human interaction in participatory performance. Spatial audio enhances the auditory environment and supports real-time control of media content and the experience. Nevertheless, AAR applied to interactive performance practices remains under-explored. This study examines how audio human-computer interaction can prompt and support actions, and how AAR can contribute to developing new kinds of interactions in participatory performance.This study investigates an AAR participatory performance based on the theater and performance practice by theater maker Augusto Boal. It draws from aspects of multi-player audio-only games and interactive storytelling. A user experience study of the performance shows that people are engaged with interactive content and interact and navigate within the spatial audio content using their whole body. Asymmetric audio cues, playing distinctive content for each participant, prompt verbal and non-verbal communication. The performative aspect was well-received and participants took on roles and responsibilities within their group during the experience.

Real-time control strategies for predenitrification - nitrification activated sludge plants biodegradation control

2001 ◽  
Vol 43 (1) ◽  
pp. 209-216 ◽  
Author(s):  
J. Suescun ◽  
X. Ostolaza ◽  
M. Garcia-Sanz ◽  
E. Ayesa
Keyword(s):  
Real Time ◽  
Pilot Plant ◽  
Control Strategies ◽  
Average Concentration ◽  
Real Time Control ◽  
Dynamic Simulations ◽  
Set Point ◽  
The Real ◽  
Time Dynamic ◽  
Time Control

This paper presents the real-time control strategies developed to regulate both the ammonia and nitrate concentration in the effluent of the new Vitoria WWTP (Spain). Nitrate control aims at the optimal use of the denitrification potential at any moment. For this purpose, the proposed control algorithm continuously adapts the internal recycle flow in order to maintain a desired nitrate set-point in the anoxic zone. Ammonia control aims at maintaining the required average concentration of ammonia in the effluent by manipulating the Dissolved Oxygen (DO) set-point. The control strategies have been based on a hierarchical structure where a high-level or supervisory control selects the set-point of the low-level or conventional controllers. The design of the controllers was carried out using the Quantitative Feedback Theory QFT for the design of robust control systems. Moving average values of some variables have been introduced in order to eliminate the perturbations associated with the daily 24-hour profiles. The controllers have been verified using long-time dynamic simulations based on a mathematical model previously calibrated in pilot plant. Influent load and temperature used in the simulations correspond to the real values measured in the full-scale WWTP during 12 months. The results obtained in the simulations show the good performance and stability of the control strategies independently from external disturbances. A short-time experimental verification of the controllers in pilot plant with real wastewater is also presented.

scholarly journals Action recognition and control of mechanical simulated arm: electromyographic signal detection

2020 ◽  
Vol 11 ◽  
pp. 10
Author(s):  
Genlai Lv
Keyword(s):  
Real Time ◽  
Recognition Accuracy ◽  
Human Motion ◽  
Real Time Control ◽  
Semg Signal ◽  
Zero Crossing ◽  
Training Time ◽  
The Real ◽  
Time Control ◽  
Emg Signal

Electromyography (EMG) signal contains a large amount of human motion information, which can be used to classify human actions. In this study, based on the detection of surface electromyography (sEMG) signal, three actions were designed, the sEMG signal was collected by the EMG acquisition system. Four feature values, including root-mean-square value, average absolute value (MAV), wavelength, and Zero crossing point, were extracted from the signal. Then these values were taken as the input of Back-Propagation neural network (BPNN) to recognize different actions, thereby realizing the real-time control of mechanical simulated arm. The experiment found that the training time of the BPNN method designed in this study was short, 11.36 s, and the average recognition accuracy rate reached 92.2%. In the real-time control experiment of mechanical simulated arm, the recognition accuracy of different actions reached more than 90%, and the running time was short. The experimental results verifies the effectiveness of the proposed method and make some contributions to the efficient control of the mechanical simulation arm.

scholarly journals A battle tank simulator for eye and hand coordination tasks under horizontal whole-body vibration

2018 ◽  
Vol 37 (1) ◽  
pp. 144-155 ◽  
Author(s):  
Luiz CA Campos ◽  
Luciano L Menegaldo
Keyword(s):  
Whole Body Vibration ◽  
Field Measurements ◽  
Dominant Frequency ◽  
Whole Body ◽  
Real Time Control ◽  
Control Software ◽  
Body Vibration ◽  
Time Control ◽  
Actuation System ◽  
Armored Vehicle

This paper describes the development of a simulator to reproduce gunner’s target tracking tasks in a main battle tank, under whole-body vibration conditions. For specifying the vibration and tracking conditions, three-degree-of-freedom acceleration was measured in a tracked armored vehicle, equipped with a 105 mm cannon, running in a battlefield test track. The electrohydraulic dynamics of the turret systems was experimentally identified as black-box autoregressive functions. A pneumatic actuation system and a real-time control software were designed to reproduce horizontal, single-axis periodic motion with the dominant frequency observed in field measurements. The control software displays the target and sight points and acquires the turret pointing command from an adapted gunner’s handle joystick. The root mean square error between target and simulated turret position allows assessing gunner’s target acquisition and tracking performance under periodic vibration.

Residual Elimination Algorithm Enhancements to Improve Foot Motion Tracking During Forward Dynamic Simulation of Gait

2012 ◽  
Author(s):  
Jennifer N. Jackson ◽  
Chris J. Hass ◽  
Benjamin J. Fregly
Keyword(s):  
Dynamic Simulation ◽  
Motion Tracking ◽  
Equations Of Motion ◽  
Human Movement ◽  
Whole Body ◽  
Dynamic Simulations ◽  
Inverse Dynamic ◽  
Motion Data ◽  
Elimination Algorithm ◽  
Contact Models

During inverse dynamic simulations of human movement, inaccuracies and noise in experimental data result in residual forces and torques acting on the pelvis [1]. These quantities are physically unrealistic but are necessary to balance the equations of motion. To circumvent this problem, Remy and Thelen developed a residual elimination algorithm (REA) that employs forward dynamic simulation to produce dynamically consistent accelerations that best agree with experimental marker motion data and satisfy the whole-body equations of motion [2]. While the kinematics are dynamically consistent and the pelvis residuals effectively eliminated, the inability of REA to reproduce foot marker motion accurately is a hindrance for applications requiring precise positioning of the feet (e.g., foot-ground contact models).

scholarly journals Real-time control of 3D virtual human motion using a depth-sensing camera for agricultural machinery training

2013 ◽  
Vol 58 (3-4) ◽  
pp. 782-789 ◽  
Author(s):  
Chengfeng Wang ◽  
Qin Ma ◽  
Dehai Zhu ◽  
Hong Chen ◽  
Zhoutuo Yang
Keyword(s):  
Real Time ◽  
Human Motion ◽  
Virtual Human ◽  
Agricultural Machinery ◽  
Real Time Control ◽  
Depth Sensing ◽  
Time Control

scholarly journals Human movement and ergonomics: An industry-oriented dataset for collaborative robotics

2019 ◽  
Vol 38 (14) ◽  
pp. 1529-1537 ◽  
Author(s):  
Pauline Maurice ◽  
Adrien Malaisé ◽  
Clélie Amiot ◽  
Nicolas Paris ◽  
Guy-Junior Richard ◽  
...  
Keyword(s):  
Machine Learning ◽  
Inertial Sensors ◽  
Human Movement ◽  
Work Conditions ◽  
Human Motion ◽  
Sensor Data ◽  
Machine Learning Techniques ◽  
Whole Body ◽  
Collaborative Robotics ◽  
Optical Motion

Improving work conditions in industry is a major challenge that can be addressed with new emerging technologies such as collaborative robots. Machine learning techniques can improve the performance of those robots, by endowing them with a degree of awareness of the human state and ergonomics condition. The availability of appropriate datasets to learn models and test prediction and control algorithms, however, remains an issue. This article presents a dataset of human motions in industry-like activities, fully labeled according to the ergonomics assessment worksheet EAWS, widely used in industries such as car manufacturing. Thirteen participants performed several series of activities, such as screwing and manipulating loads under different conditions, resulting in more than 5 hours of data. The dataset contains the participants’ whole-body kinematics recorded both with wearable inertial sensors and marker-based optical motion capture, finger pressure force, video recordings, and annotations by three independent annotators of the performed action and the adopted posture following the EAWS postural grid. Sensor data are available in different formats to facilitate their reuse. The dataset is intended for use by researchers developing algorithms for classifying, predicting, or evaluating human motion in industrial settings, as well as researchers developing collaborative robotics solutions that aim at improving the workers’ ergonomics. The annotation of the whole dataset following an ergonomics standard makes it valuable for ergonomics-related applications, but we expect its use to be broader in the robotics, machine learning, and human movement communities.

scholarly journals Analysis and Research on Human Movement in Sports Scene

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yan Wang ◽  
Yuchen Zhang ◽  
LinJun Shen ◽  
ShuMing Wang
Keyword(s):  
Body Movement ◽  
Movement Analysis ◽  
Human Movement ◽  
Human Motion ◽  
Whole Body ◽  
Human Motion Analysis ◽  
Analysis Method ◽  
Multilabel Classification ◽  
Movement Process ◽  
Rope Skipping

As a whole-body sport, skipping rope plays an increasingly important role in daily life. In rope-skipping education, due to the lack of professional teachers, the training efficiency of students is low. The rope-skipping monitoring device is heavy and expensive, and the cost of labor statistics and energy consumption are high. In order to quickly analyze the movement process of students and provide correct guidance, this article implements the movement analysis method of the human body movement process. The problem of limb posture analysis in rope skipping is transformed into a multilabel classification problem, a real-time human motion analysis method based on mobile vision is proposed, and the algorithm model is verified in the rope-skipping scene. The experimental results prove that this paper proposes the improved algorithm, which achieved the expected effect. In the analysis of rope-skipping action, the choice of hyperparameters during the experiment is introduced, and it is verified that the proposed ALSTM-LSTM can solve the problem of multilabel classification in the rope-skipping process. The accuracy rate reaches 95.1%, and it can provide the best in all indicators and good performance. It is of great significance for movement analysis and movement quality evaluation during exercise.

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