LIREC aims to establish a multi-faceted theory of artificial long-term companions (including memory, emotions, cognition, communication, learning, etc.), embody this theory in robust and innovative technology and experimentally verify both the theory and technology in real social environments. Whether as robots, social toys or graphical and mobile synthetic characters, interactive and sociable technology is advancing rapidly. However, the social, psychological and cognitive foundations and consequences of such technological artefacts entering our daily lives - at work, or in the home - are less well understood.

Key areas of the research will focus on are:

Robots and agents which build up a long term relationship with their users.

In order to maintain a long term companionship, the agent will be required to move between different forms. Forms currently under investigation are:

• Mobile robot
• Fixed robot
• Handheld device
• Fixed graphical system

This migration between these devices, and how people relate to this migration is a core element of the research.

The scenarios are to be considered preliminary ideas for showcasing the technology developed for lirec, and highlight companionship and mostly exercise migration between devices.

Spirit of the building:

1. Team buddy, mobile robot, collective memory for a lab team
2. Personal guide - for navigating around a university campus, remember appointments etc
3. In the wild - a gossip/chat robot - appears on a large screen in social area

1. Game companion for young children
2. Personal trainer (migrate to mobile robot for jogging exercises etc)
3. Welcome to the jungle - talk to game characters through a robot, robot can alternate

between real and game world

1. Fetch and carry, help with physical impairment or convenience
2. Cognitive prosthetic - memory aid for tasks etc
3. Telepresence card player - robot mediates play
4. Teaching Proxemic preferences - robot learns where to be relative to the user in different situations
5. Travelling companion - agent migration, to stay with user during home, work, shopping.

Has to:

1. Run on very different platforms
2. Reuse code across these platforms
3. 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.

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.

NASREM/NIST RCS - NASA + ESA use a generic system with their subcontractors.

In the past there have been 2 broad approaches to robot design:

• Hierarchical, model based planning = expensive to maintain accurate world state model
• Behavioural approach = less state, local decisions, liable to local minima, opaque to program

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 architecture will consist of 3 layers of abstraction:

• Level 1 - device layer, platform dependant
• Level 2 - platform dependant → logical mappings
• 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 platforms, and different implementations of the same competency will be needed for different platforms.

Example competencies:

• Face finding
• Expression recognition
• Text to speech
• Obstacle avoidance

YARP