This article reviews the state-of-the-art modeling and control techniques for aerial robots
such as quadrotor systems and presents several future research directions in this area. The …

Interaction between a robot and its environment requires perception about the environment,
which helps the robot in making a clear decision about the object type and its location. After …

We describe a learning-based approach to hand-eye coordination for robotic gras** from
monocular images. To learn hand-eye coordination for gras**, we trained a large …

This paper introduces a reinforcement learning method for exploring a corridor environment
with the depth information from an RGB-D sensor only. The robot controller achieves …

Exploration in an unknown environment is an elemental application for mobile robots. In this
paper, we outlined a reinforcement learning method aiming for solving the exploration …

Quantifying the robot's performance in terms of dexterity and maneuverability is essential for
the analysis and design of novel robot mechanisms and for the selection of appropriate …

Internal models play a key role in cognitive agents by providing on the one hand predictions
of sensory consequences of motor commands (forward models), and on the other hand …

Autonomous robots need to interact with unknown, unstructured and changing
environments, constantly facing novel challenges. Therefore, continuous online adaptation …

Within the last 10 years, new tools for assisting in the teaching and learning of academic
skills and content within the context of science have arisen. These new tools include multiple …

The design of robotic systems is largely dictated by our purely human intuition about how we
perceive the world. This intuition has been proven incorrect with regard to a number of …