69,815 research outputs found
Online Motion Generation for Mirroring Human Arm Motion
Motion planning in robotics is a very large field
of research. Many different approaches have been developed
to create smooth trajectories for robot movement. For example
there are optimization algorithms, which optimize kinematic
or dynamic properties of a trajectory. Furthermore, nonlinear
programming methods like e.g. optimal control, or polynomial
based methods are widely used for trajectory generation. Most
of these techniques are used to calculate a trajectory in advance,
or they are limited to create point-to-point motions, where the
robot needs to stop when switching to the next target point,
especially, when interpolating in rotational space. In this paper,
we combine a low-pass filter and spherical linear interpolation
to realize a velocity-limited online trajectory generator for
robot orientations in quaternion space. We use the developed
motion generator for mirroring a human arm motion with a
robot, recorded by a low frequency visual tracking. Using the
proposed method, we can replicate the motion of the operator’s
arm with very little delay and thereby achieve an easy-to-use
interface. Furthermore, as we can strictly limit the velocity
of the generated motion, the approach can safely be used in
human robot collaboration applications
Real Time Animation of Virtual Humans: A Trade-off Between Naturalness and Control
Virtual humans are employed in many interactive applications using 3D virtual environments, including (serious) games. The motion of such virtual humans should look realistic (or ‘natural’) and allow interaction with the surroundings and other (virtual) humans. Current animation techniques differ in the trade-off they offer between motion naturalness and the control that can be exerted over the motion. We show mechanisms to parametrize, combine (on different body parts) and concatenate motions generated by different animation techniques. We discuss several aspects of motion naturalness and show how it can be evaluated. We conclude by showing the promise of combinations of different animation paradigms to enhance both naturalness and control
Human motion modeling and simulation by anatomical approach
To instantly generate desired infinite realistic human motion is still a great challenge in virtual human simulation. In this paper, the novel emotion effected motion classification and anatomical motion classification are presented, as well as motion capture and parameterization methods. The framework for a novel anatomical approach to model human motion in a HTR (Hierarchical Translations and Rotations) file format is also described. This novel anatomical approach in human motion modelling has the potential to generate desired infinite human motion from a compact motion database. An architecture for the real-time generation of new motions is also propose
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