Humanoid robot

About: Humanoid robot is a research topic. Over the lifetime, 14387 publications have been published within this topic receiving 243674 citations. The topic is also known as: 🤖.

A force reflected exoskeleton-type masterarm for human-robot interaction

Abstract: Two human-robot interactions, including a haptic interaction and a teleoperated interaction, are explored with a new exoskeleton-type masterarm, in which the electric brakes with the torque sensor beams are used for force reflection. In the haptic interaction with virtual environment, the masterarm is used as a haptic device and tested to examine how the resistant torque of the electric brake for the force reflection is implemented in contact regime prior to conducting the teleoperated interaction. Two types of virtual environments, a rigid wall with high stiffness (hard contact with 10 [KN/m]) and a soft wall with low stiffness (soft contact with 0.1 [N/m]), are integrated with the masterarm for the haptic interaction. In hard contact, large force is fed back to the human operator, and makes the human operator hardly move. The electric brake with the torque sensor beam can detect the torque and its direction so that it allows free motion as well as contact motion by releasing or holding the movement of the operator. The experimental results show how the electric brake is switched from contact to free regime to allow the operator to move freely, especially when the operator intends to move toward the free regime in contact. In soft contact, the force applied to the human operator can be increased or decreased proportionally to the torque amount sensed by the torque sensor beam, thus the operator can feel the contact force proportional to the amount of the deformation during the contact. Finally, the masterarm is integrated with the humanoid robot, CENTAUR developed at Korea Institute of Science and Technology to conduct a pick-and-place task through the teleoperated interaction. It is examined that the CENTAUR as a slave robot can follow the movement of the operator.

Exploring affordances and tool use on the iCub

Abstract: One of the recurring challenges in humanoid robotics is the development of learning mechanisms to predict the effects of certain actions on objects. It is paramount to predict the functional properties of an object from “afar”, for example on a table, in a rack or a shelf, which would allow the robot to select beforehand and automatically an appropriate action (or sequence of actions) in order to achieve a particular goal. Such sensory to motor schemas associated to objects, surfaces or other entities in the environment are called affordances [1, 2] and, more recently, they have been formalized computationally under the name of object-action complexes [3] (OACs). This paper describes an approach to the acquisition of affordances and tool use in a humanoid robot combining vision, learning and control. Learning is structured to enable a natural progression of episodes that include objects, tools, and eventually knowledge of the complete task. We finally test the robot's behavior in an object retrieval task where it has to choose among a number of possible elongated tools to reach the object of interest which is otherwise out of the workspace.

The interactive effects of robot anthropomorphism and robot ability on perceived threat and support for robotics research

Abstract: The present research examines how a robot's physical anthropomorphism interacts with perceived ability of robots to impact the level of realistic and identity threat that people perceive from robots and how it affects their support for robotics research. Experimental data revealed that participants perceived robots to be significantly more threatening to humans after watching a video of an android that could allegedly outperform humans on various physical and mental tasks relative to a humanoid robot that could do the same. However, when participants were not provided with information about a new generation of robots' ability relative to humans, then no significant differences were found in perceived threat following exposure to either the android or humanoid robots. Similarly, participants also expressed less support for robotics research after seeing an android relative to a humanoid robot outperform humans. However, when provided with no information about robots' ability relative to humans, then participants showed marginally decreased support for robotics research following exposure to the humanoid relative to the android robot. Taken together, these findings suggest that very humanlike robots can not only be perceived as a realistic threat to human jobs, safety, and resources, but can also be seen as a threat to human identity and uniqueness, especially if such robots also outperform humans. We also demonstrate the potential downside of such robots to the public's willingness to support and fund robotics research.

Experimentation of Humanoid Walking Allowing Immediate Modification of Foot Place Based on Analytical Solution

Abstract: This paper proposes a method of a real-time gait planning for humanoid robots which can change stride immediately at every step. Based on an analytical solution of an inverted pendulum model, the trajectories of the COG (center of gravity) and the ZMP (zero-moment point) are parameterized by polynomials. Since their coefficients can be efficiently computed with given boundary conditions, this framework can provide a real-time walking pattern generator for humanoid robots. To handle the unexpected result caused by immediate changes of foot placement, we made single support periods as an additional trajectory parameter and the ZMP fluctuation was suppressed by mixing the opposite phase of the ZMP error. The effectiveness of our method is shown by experiments of the humanoid robot HRP-2.