A genetic algorithm approach to identify virtual object properties for sharing the feel from virtual environments

Yongyao Yan; Gregory Ruthenbeck; Karen Reynolds

doi:10.1007/978-3-662-44196-1_37

A genetic algorithm approach to identify virtual object properties for sharing the feel from virtual environments

Yongyao Yan, Gregory Ruthenbeck, Karen Reynolds

Research output: Contribution to conference › Paper › peer-review

Abstract

Haptics has provided people with new computer interaction styles across a range of applications. However, it is difficult to share haptic experiences from haptic virtual environments (HVEs). In this paper, we introduce a genetic algorithm (GA) approach, which is used to identify the virtual object’s properties (e.g. stiffness, friction coefficient and geometry parameters) based on haptic recordings, so that the haptic rendering can be reproduced without requiring the original HVE software to be deployed.

Original language	English
Pages	305-312
Number of pages	8
DOIs	https://doi.org/10.1007/978-3-662-44196-1_37
Publication status	Published - 1 Jan 2014
Event	9th International Conference, EuroHaptics 2014 - Duration: 24 Jun 2014 → …

Conference

Conference	9th International Conference, EuroHaptics 2014
Period	24/06/14 → …

Keywords

Genetic algorithm
Haptic recording
Virtual environment

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10.1007/978-3-662-44196-1_37

Cite this

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AB - Haptics has provided people with new computer interaction styles across a range of applications. However, it is difficult to share haptic experiences from haptic virtual environments (HVEs). In this paper, we introduce a genetic algorithm (GA) approach, which is used to identify the virtual object’s properties (e.g. stiffness, friction coefficient and geometry parameters) based on haptic recordings, so that the haptic rendering can be reproduced without requiring the original HVE software to be deployed.

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A genetic algorithm approach to identify virtual object properties for sharing the feel from virtual environments

Abstract

Conference

Keywords

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