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: 🤖.

RobotCub: an open framework for research in embodied cognition

Abstract: We describe a research initiative in embodied cognition that will create and exploit a 54 degree-of-freedom humanoid robot This humanoid - RobotCub is currently being designed and the final system will be made freely available to the scientific community through an open systems GNU-like general public license In addition, we describe a research agenda in cognitive systems that is based on the co-developmental learning through embodied physical interaction: exploration, manipulation, imitation, and communication This agenda borrows heavily from experience in developmental psychology and cognitive neuroscience All cognitive software associated with RobotCub will also be available under the open systems license

Development of a dynamic biped walking system for humanoid - development of a biped walking robot adapting to the humans' living floor

Abstract: In this paper, the authors introduce an anthropomorphic dynamic biped walking robot adapting to the humans' living floor. The robot has two systems: 1) a special foot system to obtain the position relative to a landing surface and the gradient of the surface during its dynamic walking; 2) an adaptive walking control system to adapt to the path surfaces with unknown shapes by utilising the information of landing surface, obtained by the foot system. Two units of the foot system WAF-3 have been developed: a biped walking robot WL-12RVII that has the foot system and the adaptive walking control system installed inside it. A walking experiment with the WL-12RVII was performed. As a result, dynamic biped walking adapting to humans' living floor with unknown shape was realised. The maximum walking speed was 1.28 s/step with a 0.3 m step length, and the adaptable deviation range was from -16 to 16 mm/step in the vertical direction, and from -3 to +3/spl deg/ in the tilt angle.

Connecting Artificial Brains to Robots in a Comprehensive Simulation Framework: The Neurorobotics Platform.

Abstract: Combined efforts in the fields of neuroscience, computer science and biology allowed to design biologically realistic models of the brain based on spiking neural networks. For a proper validation of these models, an embodiment in a dynamic and rich sensory environment, where the model is exposed to a realistic sensory-motor task, is needed. Due to the complexity of these brain models that, at the current stage, cannot deal with real-time constraints, it is not possible to embed them into a real world task. Rather, the embodiment has to be simulated as well. While adequate tools exist to simulate either complex neural networks or robots and their environments, there is so far no tool that allows to easily establish a communication between brain and body models. The Neurorobotics Platform is a new web-based environment that aims to filling this gap by offering scientists and technology developers a software infrastructure allowing them to connect brain models to detailed simulations of robot bodies and environments and to use the resulting neurorobotic systems for in-silico experimentation. In order to simplify the workflow and reduce the level of the required programming skills, the platform provides editors for the specification of experimental sequences and conditions, envi-ronments, robots, and brain-body connectors. In addition to that, a variety of existing robots and environments are provided. This work presents the architecture of the first release of the Neurorobotics Platform developed in subproject 10 “Neurorobotics” of the Human Brain Project (HBP). At the current state, the Neurorobotics Platform allows researchers to design and run basic experiments in neurorobotics using simulated robots and simulated environments linked to simplified versions of brain models. We illustrate the capabilities of the platform with three example experiments: a Braitenberg task implemented on a mobile robot, a sensory-motor learning task based on a robotic controller and a visual tracking embedding a retina model on the iCub humanoid robot. These use-cases allow to assess the applicability of the Neurorobotics Platform for robotic tasks as well as in neuroscientific experiments.

Overt visual attention for a humanoid robot

Abstract: The goal of our research is to investigate the interplay between oculomotor control, visual processing, and limb control in humans and primates by exploring the computational issues of these processes with a biologically inspired artificial oculomotor system on an anthropomorphic robot. In this paper, we investigate the computational mechanisms for visual attention in such a system. Stimuli in the environment excite a dynamical neural network that implements a saliency map, i.e., a winner-take-all competition between stimuli while simultaneously smoothing out noise and suppressing irrelevant inputs. In real-time, this system computes new targets for the shift of gaze, executed by the head-eye system of the robot. The redundant degrees-of-freedom of the head-eye system are resolved through a learned inverse kinematics with optimization criterion. We also address important issues how to ensure that the coordinate system of the saliency map remains correct after movement of the robot. The presented attention system is built on principled modules and generally applicable for any sensory modality.

Development of a bipedal humanoid robot having antagonistic driven joints and three DOF trunk

Abstract: The authors proposed the construction of a bipedal humanoid robot that has a head system with visual sensors, two hand-arm systems, 3-DOF trunk and antagonistic driven joints using the nonlinear spring mechanism, on the basis of WL-13. And we really designed and built it. In addition, as the first step to realize the dynamic cooperative motion of limbs and 3-DOF trunk, the authors developed the control algorithm and the simulation program that generates the trajectory of 3-DOF trunk for stable biped walking pattern even if the trajectories of upper and lower limbs are arbitrarily set for locomotion and manipulation respectively. Using this preset walking pattern with variable muscle tension references correspond to swing phase and stance phase, the authors performed walking experiment of dynamic walking forward and backward dynamic dance with 3-DOF trunk motion and carrying, on a flat level surface (1.28 s/step with a 0.15 m step length). As a result, the efficiency of our walking control algorithm and robot system was proved. In this paper, the mechanism of WABIAN and its control method are introduced.