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Simulating human motion using Motion Model Units – example implementation and usage

Kłodkowski Adam, Kurinov Ilya, Orzechowski Grzegorz, Mikkola Aki

Archive of Mechanical Engineering

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2022

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LXIX, nr 3

345--373

EN

Human motion is required in many simulation models. However, generating such a motion is quite complex and in industrial simulation cases represents an overhead that often cannot be accepted. There are several common file formats that are used nowadays for saving motion data that can be used in gaming engines or 3D editing software. Using such motion sets still requires considerable effort in creating logic for motion playing, blending, and associated object manipulation in the scene. Additionally, every action needs to be described with the motion designed for the target scene environment. This is where the Motion Model Units (MMU) concept was created. Motion Model Units represent a new way of transferring human motion data together with logic and scene manipulation capabilities between motion vendors and simulation platforms. The MMU is a compact software bundle packed in a standardized way, provides machine-readable capabilities and interface description that makes it interchangeable, and is adaptable to the scene. Moreover, it is designed to represent common actions in a task-oriented way, which allows simplifying the scenario creation to a definition of tasks and their timing. The underlying Motion Model Interface (MMI) has become an open standard and is currently usable in MOSIM framework, which provides the implementation of the standard for the Unity gaming engine and works on implementation for the Unreal Engine are under way. This paper presents two implementation examples for the MMU using direct C# programming, and using C# for Unity and MOSIM MMU generator as a helping tool. The key points required to build a working MMU are presented accompanied by an open-source code that is available for download and experimenting.

2

Preview Control applied for humanoid robot motion generation

Szumowski Maksymilian, Żurawska Magdalena Sylwia, Zielińska Teresa

Archives of Control Sciences

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2019

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Vol. 29, No. 1

111--132

EN

This paper presents a concept of humanoid robot motion generation using the dedicated simplified dynamic model of the robot (Extended Cart-Table model). Humanoid robot gait with equal steps length is considered. Motion pattern is obtained here with use of Preview Control method. Motion trajectories are first obtained in simulations (off-line) and then they are verified on a test-bed. Tests performed using the real robot confirmed the correctness of the method. Robot completed a set of steps without losing its balance.

3

Dynamic Motion Control: Adaptive Bimanual Grasping for a Humanoid Robot

Mellmann H., Cotugno G.

Fundamenta Informaticae

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2011

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Vol. 112, nr 1

89-101

EN

The ability to grasp objects of different size and shape is one of the most important skills of a humanoid robot. There are a lot of different approaches tackling this problem; however, there is no general solution. The complexity and the skill of a possible grasping motion depend hardly on a particular robot. In this paper we analyze the kinematic and sensory grasping abilities of the humanoid robot Nao. Its kinematic constraints and hand’s mechanical structure represent an interesting case of study due to lack of actuators for fingers and the limited computation power. After describing the platform and studying its capabilities, we propose some simple controllers and we present a benchmark based on some experimental data.

4

Some insights in path planning of small autonomous blimps

Bestaoui Y., Hima S.

Archives of Control Sciences

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2001

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Vol. 11, no. 3/4

139-166

EN

A blimp is a small airship that has no metal framework and collapses when deflated. In the first part of this paper, kinematics and dynamics modelling of small autonomous non rigid airships is presented. Euler angles and parameters are used in the formulation of this model. In the second part of the paper, path planning is introduced using helices with vertical axes. Motion generation for trim trajectories (helices with constant curvature and torsion) is presented. Then path planning using helices with quadratic curvature and torsion is described, and motion generation on these helices expressed. This motion generation takes into account the dynamics model presented.