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| lirec_notes [2009-01-06 14:51] – davegriffiths | lirec_notes [2009-01-06 15:12] – davegriffiths | ||
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| - | LIving with Robots and InteractivE Companions | + | ==== LIving with Robots and InteractivE Companions |
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| + | LIREC aims to establish a multi-faceted theory of artificial long-term companions (including memory, emotions, cognition, communication, | ||
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| + | ==Agent platforms== | ||
| + | |||
| + | The platforms currently under consideration for long term companions are: | ||
| + | * Mobile robots | ||
| + | * Fixed robots | ||
| + | * Handheld devices | ||
| + | * Fixed graphical systems | ||
| + | |||
| + | ==Migration== | ||
| + | |||
| + | An interesting feature of the research is migration betwen these platforms. Agents which need to build up a long term relationship with their users will have to switch forms depending on the needs of the user at different times. The migration of an agent between devices, and how people relate to it, is a core element of the research. | ||
| ===Scenarios=== | ===Scenarios=== | ||
| + | |||
| + | The scenarios are to be considered preliminary ideas for showcasing the technology developed for lirec, and highlight companionship and mostly exercise migration between devices. | ||
| ==Heriot Watt== | ==Heriot Watt== | ||
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| - Teaching Proxemic preferences - robot learns where to be relative to the user in different situations | - Teaching Proxemic preferences - robot learns where to be relative to the user in different situations | ||
| - Travelling companion - agent migration, to stay with user during home, work, shopping. | - Travelling companion - agent migration, to stay with user during home, work, shopping. | ||
| + | |||
| + | ===Experiment=== | ||
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| + | All scenarios are to be experimentally tested in public. | ||
| ===Architecture=== | ===Architecture=== | ||
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| ==Methodology== | ==Methodology== | ||
| In the past there have been 2 broad approaches to robot design: | In the past there have been 2 broad approaches to robot design: | ||
| - | * Heirarchical, model based planning = expensive to maintain accurate world state model | + | * Hierarchical, model based planning = expensive to maintain accurate world state model |
| * Behavioural approach = less state, local decisions, liable to local minima, opaque to program | * Behavioural approach = less state, local decisions, liable to local minima, opaque to program | ||
| This can be summed up as predictive vs reactive. | This can be summed up as predictive vs reactive. | ||
| - | Current thinking | + | The plan is to use a hybrid approach, example BIRON. Where the predictive constrains the reactive to combine local decisions with a world model. |
| The architecture will consist of 3 layers of abstraction: | The architecture will consist of 3 layers of abstraction: | ||
| - | * Level 1 - device layer, | + | * Level 1 - device layer, |
| - | * Level 2 - architecture | + | * Level 2 - platform |
| - | * Level 3 - ION, device independant | + | * Level 3 - ION, platform independent |
| - | Level 2 will provide a reference architecture with modular capabilities called competencies. Not all competencies will make sense for all architectures, and different implementations of the same competency | + | Level 2 will provide a reference architecture with modular capabilities called competencies. Not all competencies will make sense for all platforms, and different implementations of the same competency |
| Example competencies: | Example competencies: | ||
nik