Academic literature on the topic 'Whole-Body motion optimization'

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Journal articles on the topic "Whole-Body motion optimization":

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Stein, Kevin, and Katja Mombaur. "Whole-Body Dynamic Analysis of Challenging Slackline Jumping." Applied Sciences 10, no. 3 (February 6, 2020): 1094. http://dx.doi.org/10.3390/app10031094.

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Maintaining balance on a slackline is a challenging task in itself. Walking on a high line, jumping and performing twists or somersaults seems nearly impossible. Contact forces are essential to understanding how humans maintain balance in such challenging situations, but they cannot always be measured directly. Therefore, we propose a contact model for slackline balancing that includes the interaction forces and torques as well as the position of the Center of Pressure. We apply this model within an optimization framework to perform a fully dynamic motion reconstruction of a jump with a rotation of approximately 180 ° . Newton’s equations of motions are implemented as constraints to the optimization, hence the optimized motion is physically feasible. We show that a conventional kinematic analysis results in dynamic inconsistencies. The advantage of our method becomes apparent during the flight phase of the motion and when comparing the center of mass and angular momentum dynamics. With our motion reconstruction method all momentum is conserved, whereas the conventional analysis shows momentum changes of up to 30%. Furthermore, we get additional and reliable information on the interaction forces and the joint torque that allow us to further analyze slackline balancing strategies.
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KIM, JUNG-YUP, and YOUNG-SEOG KIM. "WHOLE-BODY MOTION GENERATION OF ANDROID ROBOT USING MOTION CAPTURE AND NONLINEAR CONSTRAINED OPTIMIZATION." International Journal of Humanoid Robotics 10, no. 02 (June 2013): 1350003. http://dx.doi.org/10.1142/s0219843613500035.

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This paper describes a whole-body motion generation scheme for an android robot using motion capture and an optimization method. Android robots basically require human-like motions due to their human-like appearances. However, they have various limitations on joint angle, and joint velocity as well as different numbers of joints and dimensions compared to humans. Because of these limitations and differences, one appropriate approach is to use an optimization technique for the motion capture data. Another important issue in whole-body motion generation is the gimbal lock problem, where a degree of freedom at the three-DOF shoulder disappears. Since the gimbal lock causes two DOFs at the shoulder joint diverge, a simple and effective strategy is required to avoid the divergence. Therefore, we propose a novel algorithm using nonlinear constrained optimization with special cost functions to cope with the aforementioned problems. To verify our algorithm, we chose a fast boxing motion that has a large range of motion and frequent gimbal lock situations as well as dynamic stepping motions. We then successfully obtained a suitable boxing motion very similar to captured human motion and also derived a zero moment point (ZMP) trajectory that is realizable for a given android robot model. Finally, quantitative and qualitative evaluations in terms of kinematics and dynamics are carried out for the derived android boxing motion.
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Liu, Yaliang, Xuechao Chen, Zhangguo Yu, Haoxiang Qi, and Chuanku Yi. "Single Sequential Trajectory Optimization with Centroidal Dynamics and Whole-Body Kinematics for Vertical Jump of Humanoid Robot." Biomimetics 9, no. 5 (May 2, 2024): 274. http://dx.doi.org/10.3390/biomimetics9050274.

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High vertical jumping motion, which enables a humanoid robot to leap over obstacles, is a direct reflection of its extreme motion capabilities. This article proposes a single sequential kino-dynamic trajectory optimization method to solve the whole-body motion trajectory for high vertical jumping motion. The trajectory optimization process is decomposed into two sequential optimization parts: optimization computation of centroidal dynamics and coherent whole-body kinematics. Both optimization problems converge on the common variables (the center of mass, momentum, and foot position) using cost functions while allowing for some tolerance in the consistency of the foot position. Additionally, complementarity conditions and a pre-defined contact sequence are implemented to constrain the contact force and foot position during the launching and flight phases. The whole-body trajectory, including the launching and flight phases, can be efficiently solved by a single sequential optimization, which is an efficient solution for the vertical jumping motion. Finally, the whole-body trajectory generated by the proposed optimized method is demonstrated on a real humanoid robot platform, and a vertical jumping motion of 0.5 m in height (foot lifting distance) is achieved.
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Trivedi, Urvish, Redwan Alqasemi, and Rajiv Dubey. "CARRT—Motion Capture Data for Robotic Human Upper Body Model." Sensors 23, no. 20 (October 10, 2023): 8354. http://dx.doi.org/10.3390/s23208354.

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In recent years, researchers have focused on analyzing humans’ daily living activities to study various performance metrics that humans subconsciously optimize while performing a particular task. In order to recreate these motions in robotic structures based on the human model, researchers developed a framework for robot motion planning which is able to use various optimization methods to replicate similar motions demonstrated by humans. As part of this process, it will be necessary to record the motions data of the human body and the objects involved in order to provide all the essential information for motion planning. This paper aims to provide a dataset of human motion performing activities of daily living that consists of detailed and accurate human whole-body motion data collected using a Vicon motion capture system. The data have been utilized to generate a subject-specific full-body model within OpenSim. Additionally, it facilitated the computation of joint angles within the OpenSim framework, which can subsequently be applied to the subject-specific robotic model developed MATLAB framework. The dataset comprises nine daily living activities and eight Range of Motion activities performed by ten healthy participants and with two repetitions of each variation of one action, resulting in 340 demonstrations of all the actions. A whole-body human motion database is made available to the public at the Center for Assistive, Rehabilitation, and Robotics Technologies (CARRT)-Motion Capture Data for Robotic Human Upper Body Model, which consists of raw motion data in .c3d format, motion data in .trc format for the OpenSim model, as well as post-processed motion data for the MATLAB-based model.
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Li, Jun, Haibo Gao, Yuhui Wan, Joseph Humphreys, Christopher Peers, Haitao Yu, and Chengxu Zhou. "Whole-Body Control for a Torque-Controlled Legged Mobile Manipulator." Actuators 11, no. 11 (October 22, 2022): 304. http://dx.doi.org/10.3390/act11110304.

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The task of performing locomotion and manipulation simultaneously poses several scientific challenges, such as how to deal with the coupling effects between them and how to cope with unknown disturbances introduced by manipulation. This paper presents an inverse dynamics-based whole-body controller for a torque-controlled quadrupedal manipulator capable of performing locomotion while executing manipulation tasks. Unlike existing methods that deal with locomotion and manipulation separately, the proposed controller can handle them uniformly, which can take into account the coupling effects between the base, limbs and manipulated object. The controller tracks the desired task–space motion references based on a hierarchical optimization algorithm, given a set of hierarchies that define strict priorities and the importance of weighting each task within a hierarchy. The simulation results show the robot is able to follow multiple task–space motion reference trajectories with reasonable deviation, which proved the effectiveness of the proposed controller.
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Wallmeier, Ludwig, and Lutz Wiegrebe. "Self-motion facilitates echo-acoustic orientation in humans." Royal Society Open Science 1, no. 3 (November 2014): 140185. http://dx.doi.org/10.1098/rsos.140185.

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The ability of blind humans to navigate complex environments through echolocation has received rapidly increasing scientific interest. However, technical limitations have precluded a formal quantification of the interplay between echolocation and self-motion. Here, we use a novel virtual echo-acoustic space technique to formally quantify the influence of self-motion on echo-acoustic orientation. We show that both the vestibular and proprioceptive components of self-motion contribute significantly to successful echo-acoustic orientation in humans: specifically, our results show that vestibular input induced by whole-body self-motion resolves orientation-dependent biases in echo-acoustic cues. Fast head motions, relative to the body, provide additional proprioceptive cues which allow subjects to effectively assess echo-acoustic space referenced against the body orientation. These psychophysical findings clearly demonstrate that human echolocation is well suited to drive precise locomotor adjustments. Our data shed new light on the sensory–motor interactions, and on possible optimization strategies underlying echolocation in humans.
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Murooka, Masaki, Kei Okada, and Masayuki Inaba. "Optimization-Based Posture Generation for Whole-Body Contact Motion by Contact Point Search on the Body Surface." IEEE Robotics and Automation Letters 5, no. 2 (April 2020): 2905–12. http://dx.doi.org/10.1109/lra.2020.2974689.

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Kim, Joo H. "Optimization of throwing motion planning for whole-body humanoid mechanism: Sidearm and maximum distance." Mechanism and Machine Theory 46, no. 4 (April 2011): 438–53. http://dx.doi.org/10.1016/j.mechmachtheory.2010.11.019.

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Tian, Yuan, and Feng Gao. "Efficient motion generation for a six-legged robot walking on irregular terrain via integrated foothold selection and optimization-based whole-body planning." Robotica 36, no. 3 (November 6, 2017): 333–52. http://dx.doi.org/10.1017/s0263574717000418.

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SUMMARYIn this paper, an efficient motion planning method is proposed for a six-legged robot walking on irregular terrain. The method provides the robot with fast-generated free-gait motions to traverse the terrain with medium irregularities. We first of all introduce our six-legged robot with legs in parallel mechanism. After that, we decompose the motion planning problem into two main steps: first is the foothold selection based on a local footstep cost map, in which both terrain features and the robot mobility are considered; second is a whole-body configuration planner which casts the problem into a general convex optimization problem. Such decomposition reduces the complexity of the motion planning problem. Along with the two-step planner, discussions are also given in terms of the robot-environmental relationship, convexity of constraints and robot rotation integration. Both simulations and experiments are carried out on typical irregular terrains. The results demonstrate effectiveness of the planning method.
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Zuo, Weilong, Junyao Gao, Jingwei Cao, Xilong Xin, Mingyue Jin, and Xuechao Chen. "Whole-Body Dynamics-Based Aerial Fall Trajectory Optimization and Landing Control for Humanoid Robot." Biomimetics 8, no. 6 (October 1, 2023): 460. http://dx.doi.org/10.3390/biomimetics8060460.

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When humanoid robots work in human environments, falls are inevitable due to the complexity of such environments. Current research on humanoid robot falls has mainly focused on falls on the ground, with little research on humanoid robots falling from the air. In this paper, we employ an extended state variable formulation that directly maps from the high-level motion strategy space to the full-body joint space to optimize the falling trajectory in order to protect the robot when falling from the air. In order to mitigate the impact force generated by the robot’s fall, during the aerial phase, we employ simple proportion differentiation (PD) control. In the landing phase, we optimize the optimal contact force at the contact point using the centroidal dynamics model. Based on the contact force, the changes to the end-effector positions are solved using a dual spring–damper model. In the simulation experiments, we conduct three comparative experiments, and the simulation results demonstrate that the robot can safely fall 1.5 m from the ground at a pitch angle of 45°. Finally, we experimentally validate the methods on an actual robot by performing a side-fall experiment. The experimental results show that the proposed trajectory optimization and motion control methods can provide excellent shock absorption for the impact generated when a robot falls.

Dissertations / Theses on the topic "Whole-Body motion optimization":

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Gomes, Junior Waldez Azevedo. "Improving Ergonomics Through Physical Human-Robot Collaboration." Electronic Thesis or Diss., Université de Lorraine, 2021. http://www.theses.fr/2021LORR0208.

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Cette thèse vise à fournir des outils pour améliorer l'ergonomie dans les environnements de travail. Certaines activités dans l'industrie sont couramment exécutées par les travailleurs de manière non ergonomique, ce qui peut entraîner des troubles musculo-squelettiques à court ou à long terme. Les troubles musculo-squelettiques (TMS) liés au travail constituent un problème de santé majeur dans le monde entier, qui représente également des coûts importants pour la société et les entreprises. On sait que les TMS sont causées par de multiples facteurs, tels que des mouvements répétitifs, une force excessive et des postures corporelles non ergonomiques. Il n'est pas surprenant que les environnements de travail présentant de tels facteurs puissent présenter une incidence de TMS jusqu'à 3 ou 4 fois plus élevée que dans la population générale. Notre approche consiste à évaluer le mouvement humain, à l'optimiser et à intervenir sur la tâche en fonction du mouvement optimisé. Pour évaluer l'ergonomie de la posture du corps, nous avons développé une simulation de modèle humain numérique (DHM en anglais) capable de reproduire les mouvements du corps entier. Dans la simulation, le mouvement initial peut être amélioré de manière itérative, jusqu'à l'obtention d'un mouvement ergonomique optimal du corps entier. Nous pensons qu'un robot en interaction physique avec un humain pourrait conduire ce dernier vers des mouvements plus ergonomiques du corps entier, voire vers un mouvement ergonomiquement optimal. Pour concevoir un contrôleur de robot qui influence la posture du corps, nous étudions d'abord le comportement moteur de l'homme dans une étude de co-manipulation entre humains. Dans cette étude, nous avons observé des modèles de comportement moteur qui ont été utilisés pour concevoir un contrôleur de collaboration pour l'interaction physique homme-robot (pHRI en anglais). L'étude de co-manipulation a ensuite été exécutée par un humain collaborant avec un robot Franka Panda
This thesis aims to provide tools for improving ergonomics at work environments. Some work activities in industry are commonly executed by workers in a non-ergonomic fashion, which may lead to musculoskeletal disorders in the short or in the long term.Work-related Musculoskeletal Disorders (WMSDs) are a major health issue worldwide, that also represents important costs both for society and companies. WMSDs are known to be caused by multiple factors, such as repetitive motion, excessive force, and awkward, non-ergonomic body postures. Not surprisingly, work environments with such factors may present an incidence of WMSDs of up to 3 or 4 times higher than in the overall population.Here, our approach is to evaluate the human motion with respect to ergonomics indexes, optimize the motion, and intervene on the task based on the optimized motion.To evaluate the body posture ergonomics, we developed a Digital Human Model (DHM) simulation capable of replaying whole-body motions.In simulation, the initial movement can be iteratively improved, until an optimal ergonomic whole-body motion is obtained.We make the case that a robot in physical interaction with a human could drive the human towards more ergonomic whole-body motions, possibly to an ergonomically optimal motion. To design a robot controller that influences the body posture, we first investigate the human motor behavior in a human-human co-manipulation study. In this human dyad study, we observed motor behavior patterns that were used to design a collaboration controller for physical human-robot interaction (pHRI). In a new study, the same co-manipulation task was then executed by humans collaborating with a Franka Emika Panda robot

Book chapters on the topic "Whole-Body motion optimization":

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Meng, Xiang, Zelin Huang, Qian Liang, Yue Dong, Zhifa Gao, Lianqiang Han, Junhang Lai, et al. "Optimization of Whole-Body Motion for Humanoid Robot Walking Down Stairs with Small Joint Range of Motion." In Advances in Mechanism and Machine Science, 859–68. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-45770-8_85.

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Conference papers on the topic "Whole-Body motion optimization":

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Modugno, Valerio, Gabriele Nava, Daniele Pucci, Francesco Nori, Giuseppe Oriolo, and Serena Ivaldi. "Safe trajectory optimization for whole-body motion of humanoids." In 2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids). IEEE, 2017. http://dx.doi.org/10.1109/humanoids.2017.8246958.

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Pösse, S., F. Büther, M. Schäfers, and KP Schäfers. "Optical Flow Parameter Optimization for Whole-body PET Motion Detection." In NuklearMedizin 2019. Georg Thieme Verlag KG, 2019. http://dx.doi.org/10.1055/s-0039-1683526.

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Posse, Stefanie, Florian Buther, Michael Schafers, and Klaus P. Schafers. "Optimization of Optical Flow Parameters for Whole-body PET Motion Correction." In 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC). IEEE, 2018. http://dx.doi.org/10.1109/nssmic.2018.8824731.

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Li, Qi, Letian Qian, Peng Sun, and Xin Luo. "Energy-Efficient Dynamic Motion Planning of Quadruped Robots via Whole-body Nonlinear Trajectory Optimization." In 2022 IEEE International Conference on Mechatronics and Automation (ICMA). IEEE, 2022. http://dx.doi.org/10.1109/icma54519.2022.9855898.

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Xin, Xilong, Junyao Gao, Jingwei Cao, Jiongnan Liu, Taiping Wu, Mingyue Jin, and Weilong Zuo. "Whole body motion control strategy of humanoid robot based on double-layer quadratic optimization." In 2023 8th International Conference on Robotics and Automation Engineering (ICRAE). IEEE, 2023. http://dx.doi.org/10.1109/icrae59816.2023.10458483.

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Kim, Joo H., Yujiang Xiang, Rajankumar Bhatt, Jingzhou Yang, Hyun-Joon Chung, Amos Patrick, Jasbir S. Arora, and Karim Abdel-Malek. "Efficient ZMP Formulation and Effective Whole-Body Motion Generation for a Human-Like Mechanism." In ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/detc2008-49925.

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An approach of generating dynamic biped motions of a human-like mechanism is proposed. An alternative and efficient formulation of the Zero-Moment Point for dynamic balance and the approximated ground reaction forces/moments are derived from the resultant reaction loads, which includes the gravity, the externally applied loads, and the inertia. The optimization problem is formulated to address the redundancy of the human task, where the general biped and task-specific constraints are imposed depending on the task requirements. The proposed method is fully predictive and generates physically feasible human-like motions from scratch; it does not require any input reference from motion capture or animation. The resulting generated motions demonstrate how a human-like mechanism reacts effectively to different external load conditions in performing a given task by showing realistic features of cause and effect. In addition, the energy-optimality of the upright standing posture is numerically verified among infinite feasible static biped postures without self contact. The proposed formulation is beneficial to motion planning, control, and physics-based simulation of humanoids and human models.
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Jin, Mingyue, Junyao Gao, Junhang Lai, Xiaokun Jin, Weilong Zuo, Jingwei Cao, and Xilong Xin. "Low-centroid Crawling Motion for Humanoid Robot Based on Whole-body Dynamics and Trajectory Optimization." In 2022 7th International Conference on Robotics and Automation Engineering (ICRAE). IEEE, 2022. http://dx.doi.org/10.1109/icrae56463.2022.10056163.

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Munaretto, Joseph M., Jill L. McNitt-Gray, and Henryk Flashner. "Experimentally Based Modeling of Whole Body Movement During Contact." In ASME 2008 International Mechanical Engineering Congress and Exposition. ASMEDC, 2008. http://dx.doi.org/10.1115/imece2008-67736.

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In this paper, we investigated how the assumption of fixed segment lengths in two dimensional whole body dynamic models limits accuracy in reproducing experimental reaction forces and observed kinematics. A six segment whole body dynamic model of the musculoskeletal system was developed to simulate the measured forces and kinematic data during the contact phase of two somersaulting tasks performed by two Olympic level divers. Initial conditions and foot-surface model parameters were refined using optimization to ensure that change in whole body center of mass (CM) linear and angular momenta satisfied the impulse/momentum relationship for both dives and divers. Simulation results indicate that the assumption of fixed segment lengths increases error in prediction of the CM trajectory in the sagittal plane. Sensitivity analysis shows that a foot/surface model high in stiffness is more accurate in reproducing observed foot metatarsal displacement but is also more sensitive to the velocity of the metatarsals at contact than a less stiff foot-surface model. As a result, the assumption of a fixed foot segment length also affects the process of optimizing the initial conditions and foot-surface parameters. These findings suggest that a 2D representation of segment motion using fixed segment lengths is limited accuracy because the fixed length representation of segment kinematics does not reflect out of plane motion. Tracking the effect of error introduced by input kinematics on model performance is essential in the process of validating a 2D model of human movement during contact with the environment.
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Il-Hwan Park, Kook-Jin Choi, and Dae Sun Hong. "Optimization and generalization of whole-body cooperative motion of a humanoid robot using a genetic algorithm and neural networks." In 2007 International Conference on Control, Automation and Systems. IEEE, 2007. http://dx.doi.org/10.1109/iccas.2007.4406825.

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Kim, Joo H., Karim Abdel-Malek, Yujiang Xiang, Jingzhou James Yang, and Jasbir S. Arora. "Motion Planning Under External Constraints for Redundant Dynamic Systems." In ASME 2010 Dynamic Systems and Control Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/dscc2010-4275.

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Dynamics of mechanical systems during motion usually involves reaction forces and moments due to the interaction with external objects or constraints from the environment. The problem of predicting the external reaction loads under rigid-body assumption has not been addressed extensively in the literature in terms of optimal motion planning and simulation. We propose a formulation of determining the external reaction loads for redundant systems motion planning. For dynamic equilibrium, the resultant reaction loads that include the effects of inertia, gravity, and general applied loads, are distributed to each contact point. Unknown reactions are determined along with the system configuration at each time step using iterative nonlinear optimization algorithm. The required actuator torques as well as the motion trajectories are obtained while satisfying given constraints. The formulation is applied to several example motions of multi-rigid-body systems such as a simple welding manipulator and a highly articulated whole-body human mechanism. The example results are compared with the cases where the reactions are pre-assigned.

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