Voodle
Tool Summary
General Purpose Information | |
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Year of First Releaseⓘ The year a tool was first publicly released or discussed in an academic paper. | 2017 |
Platformⓘ The OS or software framework needed to run the tool. | NodeJS |
Availabilityⓘ If the tool can be obtained by the public. | Available |
Licenseⓘ Tye type of license applied to the tool. | Unknown |
Venueⓘ The venue(s) for publications. | ACM DIS |
Intended Use Caseⓘ The primary purposes for which the tool was developed. | Prototyping, Communication |
Hardware Control Information | |
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Haptic Categoryⓘ The general types of haptic output devices controlled by the tool. | Force Feedback |
Hardware Abstractionⓘ How broad the type of hardware support is for a tool.
| Bespoke |
Device Namesⓘ The hardware supported by the tool. This may be incomplete. | CuddleBit |
Body Positionⓘ Parts of the body where stimuli are felt, if the tool explicitly shows this. | N/A |
Interaction and Interface Information | |
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Driving Featureⓘ If haptic content is controlled over time, by other actions, or both. | Action |
Effect Localizationⓘ How the desired location of stimuli is mapped to the device.
| Device-centric |
Media Supportⓘ Support for non-haptic media in the workspace, even if just to aid in manual synchronization. | None |
Iterative Playbackⓘ If haptic effects can be played back from the tool to aid in the design process. | Yes |
Design Approachesⓘ Broadly, the methods available to create a desired effect.
| Process |
Interaction Metaphorsⓘ Common UI metaphors that define how a user interacts with a tool.
| Demonstration |
Storageⓘ How data is stored for import/export or internally to the software. | None |
Connectivityⓘ How the tool can be extended to support new data, devices, and software. | None |
Additional Information
While Voodle is primarily meant to control 1 DoF robots called “CuddleBits”, it can also be used for haptic prototyping. The frequency and amplitude of a user’s voice is used to drive the output of the system. Each parameter is normalized and used to create a weighted average with the bias value set by the user. The user can then add random noise to the system and scale and smooth the resulting output. The mapping of voice input to motor output occurs in real time.
For more information, consult the DIS’17 paper and the GitHub repository.