Cognitive robots can cope with complex environments and unexpected situations. They are equipped with rich sensors that they interpret to perceive their environment. Cognitive robots act goal-oriented by making plans, can actively explore their environment, and identify opportunities for actions. In this way, they achieve robustness in dynamic environments. Cognitive robots don’t work in isolation, but in close interaction with other technical systems and humans. They are able to improve their behavior through learning.
Key challenges when developing cognitive robots are the systematic treatment of uncertainty, the semantic modeling of the robot environment, the identification of suitable learning methods, and the design of intuitive user interfaces. To master these challenges, we employ techniques from Probabilistic Robotics, Artificial Intelligence, and Machine Learning.
Through numerous projects, IAIS has experience in particular in the area of field robotics.