Robocup 2023-2024 ROSbag Dataset.

Area of Science:

• Robotics
• Artificial Intelligence
• Human-Robot Interaction

Background:

• Autonomous robots are increasingly deployed in complex, dynamic environments.
• Evaluating robot performance in social and navigational tasks with human interaction is crucial.
• Standardized datasets are essential for benchmarking and advancing robot capabilities.

Purpose of the Study:

• To present a comprehensive dataset from the TIAGo robot during RoboCup competitions.
• To facilitate research on autonomous robot behavior in social tasks and navigation.
• To provide valuable data for analyzing human-robot interaction in realistic scenarios.

Main Methods:

• Data collection using the TIAGo robot equipped with RGB-D camera, laser scanner, and microphone.
• Recording of sensory data and robot planning behavior in ROSbag files.
• Capturing third-person video perspectives of task execution during competitions.

Main Results:

• A rich dataset comprising sensory information, behavioral data, and visual recordings.
• Data covers autonomous robot performance in social interactions and navigation.
• The dataset documents robot behavior in dynamic environments with human presence.

Conclusions:

• The dataset offers a valuable resource for researchers in robotics and AI.
• It enables in-depth analysis of autonomous systems in human-centric environments.
• This data can drive advancements in robot learning, planning, and social navigation.