This dataset comprises three degrees of freedom (3 DOF) sensory data and simulation data collected from a Kinova robotic arm. The sensory data includes real-time measurements from the robotic arm’s joint positions, velocities, and torques, providing a detailed account of the arm’s dynamic behavior. The dataset also includes simulated data generated using a high-fidelity physics engine, accurately modeling the Kinova arm’s kinematics and dynamics under various operational scenarios.

The instantaneous state (situation) of the game was constituted by four values: the cart position, the cart speed, the pole angle to the vertical axis, and the pole angular velocity.

For each action taken by the human player in the game, a tuple containing the four values representing the current game situation, along with the action and reward obtained (utility), is recorded as a situation-decision-utility (SDU) tuple.

3 types of actions have been recorded: Move left (-1), move rght (1) and no action (0).

Flight data recorded during experiment.

<p>The technique of electrical impedance tomography (EIT) has been recognized as a promising method to design tactile sensors with continuous sensing capability over a large area. The mechanism of electrical impedance tomography allows reconstructing tactile information within the sensing area based on measurements made only at the boundary. However, spatial performance of EIT-based tactile sensors has demonstrated location dependency in previous reports, which severely affects correct interpretation of tactile stimuli.