Autonomous and Social Robotics

Autonomous and social robotics refers to a branch of robotics that combines a robot’s ability to act independently with its capacity to interact socially with humans.

An autonomous robot is capable of perceiving its environment, making decisions, and acting without direct human intervention, thanks to sensors, artificial intelligence, and processing algorithms.

The social dimension allows the robot to recognize non-verbal cues such as facial expressions, voice, or gestures, enabling it to adapt to the user and interact in a natural, empathetic, and meaningful way.

When a robot is both autonomous and social, it can not only operate independently in its environment but also establish smooth and intuitive interactions with humans.

Autonomous Robotics

Autonomous robotics relies on the integration of various technologies that enable a robot to operate independently in complex environments. At the core of this autonomy are localization and control systems, which allow the robot to orient itself and move with precision. Tools such as LIDAR sensors, brushless motors, and control techniques are used to manage movement and ensure stability. SLAM technology (Simultaneous Localization and Mapping) enables the robot to map an unknown environment while simultaneously determining its own position within it.

Another key challenge is human-robot collaboration, which involves enabling robots to operate effectively in environments shared with people. This requires the robot to interpret its surroundings by extracting semantic information and navigating through dynamic, uncertain, and unstructured spaces. This capability is essential for safe and fluid human-machine interaction.

Finally, the development of autonomous robotics is greatly supported by the use of robotic middleware such as ROS2 (Robot Operating System) and µROS, which provide standardized software architecture. These tools facilitate the integration of different system components (sensors, motors, navigation algorithms), while also enabling shared mapping and communication between robots.

Some examples of applications:

  • Autonomous delivery robots for indoor or outdoor use

  • Service robots in hospitals or hotels

  • Autonomous drones for mapping or surveillance

  • Autonomous agricultural robots

  • Mobile industrial inspection robots