Description

Robots interacting with humans for a long period of time (e.g. a week, a month, a year) should be able to remember their experiences and proactively reflect on them to find new ways to perform better. This project will focus on investigating how to integrate different types of robot long-term memories, with special attention to proposing novel knowledge-based approaches to proactive and explainable robot experiences introspection to enhance the performance of the robot in the long-term.

The work is under the scope of the following projects:

• ARISE: Advanced AI and RobotIcS for autonomous task pErformance (web)