Combining analytical inverse kinematics with example postures to generate virtual human whole body reaching postures

Author(s):  
Shilei Li ◽  
Jiahong Liang ◽  
Guang Liu ◽  
Yong Zhang
Proceedings ◽  
2020 ◽  
Vol 49 (1) ◽  
pp. 60
Author(s):  
Sohei Washino ◽  
Akihiko Murai ◽  
Hirotoshi Mankyu ◽  
Yasuhide Yoshitake

We examined the association between changes in swimming velocity, vertical center of mass (CoM) position, and projected frontal area (PFA) during maximal 200-m front crawl. Three well-trained male swimmers performed a single maximal 200-m front crawl in an indoor 25-m pool. Three-dimensional (3D) shape data of the whole body were fitted to 3D motion data during swimming by using inverse kinematics computation to estimate PFA accurately. Swimming velocity decreased, the vertical CoM position was lowered, and PFA increased with swimming distance. There were significant correlations between swimming velocity and vertical CoM position (|r| = 0.797–0.982) and between swimming velocity and PFA (|r| = 0.716–0.884) for each swimmer. These results suggest that descent of the swimmer’s body and increasing PFA with swimming distance are associated with decreasing swimming velocity, although the causal factor remains unclear.


2015 ◽  
Vol 12 (03) ◽  
pp. 1550031 ◽  
Author(s):  
Peter Kaiser ◽  
Nikolaus Vahrenkamp ◽  
Fabian Schültje ◽  
Júlia Borràs ◽  
Tamim Asfour

Humanoid robots that have to operate in cluttered and unstructured environments, such as man-made and natural disaster scenarios, require sophisticated sensorimotor capabilities. A crucial prerequisite for the successful execution of whole-body locomotion and manipulation tasks in such environments is the perception of the environment and the extraction of associated environmental affordances, i.e., the action possibilities of the robot in the environment. We believe that such a coupling between perception and action could be a key to substantially increase the flexibility of humanoid robots. In this paper, we approach the affordance-based generation of whole-body actions for stable locomotion and manipulation. We incorporate a rule-based system to assign affordance hypotheses to visually perceived environmental primitives in the scene. These hypotheses are then filtered using extended reachability maps that carry stability information, for identifying reachable affordance hypotheses. We then formulate the hypotheses in terms of a constrained inverse kinematics problem in order to find whole-body configurations that utilize a chosen set of hypotheses. The proposed methods are implemented and tested in simulated environments based on RGB-D scans as well as on a real robotic platform.


2020 ◽  
Vol 34 (21-22) ◽  
pp. 1442-1454
Author(s):  
Yuya Hakamata ◽  
Satoki Tsuichihara ◽  
Gustavo Alfonso Garcia Ricardez ◽  
Jun Takamatsu ◽  
Tsukasa Ogasawara

2019 ◽  
Vol 17 (01) ◽  
pp. 1950035
Author(s):  
Iori Kumagai ◽  
Mitsuharu Morisawa ◽  
Shin’ichiro Nakaoka ◽  
Fumio Kanehiro

In this paper, we propose a locomotion planning framework for a humanoid robot with stable whole-body collision avoidance motion, which enables the robot to traverse an unknown narrow space on the spot based on environmental measurements. The key idea of the proposed method is to reduce a large computational cost for the whole-body locomotion planning by utilizing global footstep planning results and its centroidal trajectory as a guide. In the global footstep planning phase, we modify the bounding box of the robot approximating the centroidal sway amplitude of the candidate footsteps. This enables the planner to obtain appropriate footsteps and transition time for next whole-body motion planning. Then, we execute sequential whole-body motion planning by prioritized inverse kinematics considering collision avoidance and maintaining its ZMP trajectory, which enables the robot to plan stable motion for each step in 223[Formula: see text]ms at worst. We evaluated the proposed framework by a humanoid robot HRP-5P in the dynamic simulation and the real world. The major contribution of our paper is solving the problem of increasing computational cost for whole-body motion planning and enabling a humanoid robot to execute adaptive on-site locomotion planning in an unknown narrow space.


1996 ◽  
Vol 5 (4) ◽  
pp. 402-415
Author(s):  
Sunil K. Singh ◽  
Steven D. Pieper ◽  
Jethran Guinness ◽  
Dan O. Popa

This paper addresses the modeling and computational issues associated with the control and coordination of head, eyes, and facial expressions of virtual human actors. The emphasis, as much as possible, is on using accurate physics-based computations for motion computation. Some key issues discussed in this work include the use of kinematics and inverse kinematics, trajectory planning, and the use of finite element methods to model soft tissue deformations.


2021 ◽  
Vol 8 ◽  
Author(s):  
Luca Rossini ◽  
Enrico Mingo Hoffman ◽  
Arturo Laurenzi ◽  
Nikos G. Tsagarakis

Most of the locomotion and contact planners for multi-limbed robots rely on a reduction of the search space to improve the performance of their algorithm. Posture generation plays a fundamental role in these types of planners providing a collision-free, statically stable whole-body posture, projected onto the planned contacts. However, posture generation becomes particularly tedious for complex robots moving in cluttered environments, in which feasibility can be hard to accomplish. In this work, we take advantage of the kinematic structure of a multi-limbed robot to present a posture generator based on hierarchical inverse kinematics and contact force optimization, called the null-space posture generator (NSPG), able to efficiently satisfy the aforementioned requisites in short times. A new configuration of the robot is produced through conservatively altering a given nominal posture exploiting the null-space of the contact manifold, satisfying geometrical and kinetostatics constraints. This is achieved through an adaptive random velocity vector generator that lets the robot explore its workspace. To prove the validity and generality of the proposed method, simulations in multiple scenarios are reported employing different robots: a wheeled-legged quadruped and a biped. Specifically, it is shown that the NSPG is particularly suited in complex cluttered scenarios, in which linear collision avoidance and stability constraints may be inefficient due to the high computational cost. In particular, we show an improvement of performances being our method able to generate twice feasible configurations in the same period. A comparison with previous methods has been carried out collecting the obtained results which highlight the benefits of the NSPG. Finally, experiments with the CENTAURO platform, developed at Istituto Italiano di Tecnologia, are carried out showing the applicability of the proposed method to a real corridor scenario.


1993 ◽  
Vol 2 (1) ◽  
pp. 82-86 ◽  
Author(s):  
Norman I. Badler ◽  
Michael J. Hollick ◽  
John P. Granieri

We track, in real-time, the position and posture of a human body, using a minimal number of six DOF sensors to capture full body standing postures. We use four sensors to create a good approximation of a human operator's position and posture, and map it on to our articulated computer graphics human model. The unsensed joints are positioned by a fast inverse kinematics algorithm. Our goal is to realistically recreate human postures while minimally encumbering the operator.


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