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lirec_notes [2009-01-06 15:08] – davegriffiths | lirec_notes [2009-01-06 15:28] – davegriffiths | ||
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LIREC aims to establish a multi-faceted theory of artificial long-term companions (including memory, emotions, cognition, communication, | LIREC aims to establish a multi-faceted theory of artificial long-term companions (including memory, emotions, cognition, communication, | ||
- | ==Agent platforms, and migration between them== | + | ==Links== |
- | An interesting feature of agents which need to build up a long term relationship with their users will be movement between different platforms. | + | |
+ | http:// | ||
+ | |||
+ | ==Agent platforms== | ||
+ | |||
+ | The platforms currently under consideration for long term companions | ||
* Mobile robots | * Mobile robots | ||
* Fixed robots | * Fixed robots | ||
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* Fixed graphical systems | * Fixed graphical systems | ||
- | This migration | + | ==Migration== |
+ | |||
+ | An interesting feature of the research is migration | ||
===Scenarios=== | ===Scenarios=== | ||
- | The scenarios are to be considered preliminary ideas for showcasing | + | In order to test and showcase |
==Heriot Watt== | ==Heriot Watt== | ||
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between real and game world | between real and game world | ||
- | ==University of Hertfordshire== | + | ==The University of Hertfordshire== |
- Fetch and carry, help with physical impairment or convenience | - Fetch and carry, help with physical impairment or convenience | ||
- Cognitive prosthetic - memory aid for tasks etc | - Cognitive prosthetic - memory aid for tasks etc | ||
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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. | ||
+ | |||
+ | ===Experimental testing=== | ||
+ | |||
+ | All scenarios are to be experimentally tested in public. | ||
===Architecture=== | ===Architecture=== | ||
- | Has to: | + | The technology developed for lirec is shared between the research partners, and has to: |
- Run on very different platforms | - Run on very different platforms | ||
- Reuse code across these platforms | - Reuse code across these platforms | ||
- Support migration at runtime between platforms | - Support migration at runtime between platforms | ||
- | |||
- | Platforms can consist of 4 main types, mobile robot, fixed robot, handheld device or fixed graphical system. Each has it's inherent restrictions. | ||
==Existing robot architectures== | ==Existing robot architectures== | ||
- | In the whole, there is a lack of sharing of this kind of technology. This is partly because generalising is hard in this field, considering all types of robots possible. However, Lirec has to generalise as it's using a wide variety of architectures. | + | In the whole, there has historically been a lack of sharing of this kind of technology. This is partly because generalising is hard, considering all types of robots possible. However, Lirec has to generalise as it's using a wide variety of architectures |
- | NASREM/NIST RCS - NASA + ESA use a generic system with their subcontractors. | + | While some existing architectures are available, none of them address the needs of lirec, given the focus: |
+ | | ||
+ | - Working across different platforms | ||
==Methodology== | ==Methodology== | ||
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This can be summed up as predictive vs reactive. | This can be summed up as predictive vs reactive. | ||
- | 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 plan is to use a hybrid approach, example |
The architecture will consist of 3 layers of abstraction: | The architecture will consist of 3 layers of abstraction: | ||
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* Obstacle avoidance | * Obstacle avoidance | ||
- | YARP | + | [[http:// |