This use case will focus on testing assisting living scenarios with a mobile manipulator taking the role of a companion robot. This is a highly demanding use case where the human factor is of paramount importance, with safety and agile performance critical.

A distributed edge computing (on the robot) architecture will be applied covering a range of AI algorithms for human detection and tracking, face recognition, speech interaction, object identification, adaptive motion and task planning.

The adoption of a cloud-edge hybrid architecture will positively impact the number of new objects and people detected by the robot, task execution accuracy, and perception abilities, as well as improve safety by reducing all kinds of collisions.

The use case will be inspired by the ALMI and OpenDR projects, whereas all experiments will be performed under lab conditions at PAL ROBOTICS facilities, with the TIAGo robot.

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