Space robotics is the new frontier in space research community, envisioned to accomplish many challenging objectives for the next generation space missions. Fundamentally, space robotics operation can be broadly classified into three categories. e.g. in-orbit operation, planetary exploration, and autonomous space transportation for interplanetary and deep space missions.

Collaborative UAVs, or drones, consist of a novel aerial robotic team that will possess the capability to autonomously conduct infrastructure inspection and maintenance tasks, while additionally providing intuitive and user-friendly interfaces to human-operators.

The area of Machine Learning for Robotics studies algorithms that will allow a robot to acquire novel skills or adapt to a changing environment or to an alternating aim of a mission to be accomplished.

The area of inspection robotics includes the development and utilization of robotic setups for enabling the aerial inspection and interaction with the aging infrastructure. Such robotic solutions span from the utilization of Unmanned Aerial Vehicles (UAVs) for the inspection and maintenance of industrial infrastructures, buildings.

Unmanned Ground Vehicles (UGVs) are robotic systems operating on the ground, that are capable of navigating autonomously to accomplish a variety of missions, based solely on onboard sensory feedback. UGVs come in various forms, from small-wheeled robots (turtles, huskies etc.) to large vehicles (autonomous cars, autonomous trucks, and wheel-loaders in mines etc.) and bio-inspired designs such as humanoids, quadrupeds etc.

Robotic Vision is a rapidly developing area in robotics that aims towards the utilization of computational algorithms on image data for enabling a proper perception of the environment, smooth path planning, obstacle avoidance, material handling, interaction with other robots and humans, and in general to increase the robustness and the safety of the robotic workers.