Humanoid robot

About: Humanoid robot is a(n) research topic. Over the lifetime, 14387 publication(s) have been published within this topic receiving 243674 citation(s). The topic is also known as: 🤖.

MonoSLAM: Real-Time Single Camera SLAM

Abstract: We present a real-time algorithm which can recover the 3D trajectory of a monocular camera, moving rapidly through a previously unknown scene. Our system, which we dub MonoSLAM, is the first successful application of the SLAM methodology from mobile robotics to the "pure vision" domain of a single uncontrolled camera, achieving real time but drift-free performance inaccessible to structure from motion approaches. The core of the approach is the online creation of a sparse but persistent map of natural landmarks within a probabilistic framework. Our key novel contributions include an active approach to mapping and measurement, the use of a general motion model for smooth camera movement, and solutions for monocular feature initialization and feature orientation estimation. Together, these add up to an extremely efficient and robust algorithm which runs at 30 Hz with standard PC and camera hardware. This work extends the range of robotic systems in which SLAM can be usefully applied, but also opens up new areas. We present applications of MonoSLAM to real-time 3D localization and mapping for a high-performance full-size humanoid robot and live augmented reality with a hand-held camera

Series elastic actuators

Abstract: It is traditional to make the interface between an actuator and its load as stiff as possible. Despite this tradition, reducing interface stiffness offers a number of advantages, including greater shock tolerance, lower reflected inertia, more accurate and stable force control, less inadvertent damage to the environment, and the capacity for energy storage. As a trade-off, reducing interface stiffness also lowers zero motion force bandwidth. In this paper, the authors propose that for natural tasks, zero motion force bandwidth isn't everything, and incorporating series elasticity as a purposeful element within the actuator is a good idea. The authors use the term elasticity instead of compliance to indicate the presence of a passive mechanical spring in the actuator. After a discussion of the trade-offs inherent in series elastic actuators, the authors present a control system for their use under general force or impedance control. The authors conclude with test results from a revolute series-elastic actuator meant for the arms of the MIT humanoid robot Cog and for a small planetary rover.

The development of Honda humanoid robot

Abstract: In this paper, we present the mechanism, system configuration, basic control algorithm and integrated functions of the Honda humanoid robot. Like its human counterpart, this robot has the ability to move forward and backward, sideways to the right or the left, as well as diagonally. In addition, the robot can turn in any direction, walk up and down stairs continuously. Furthermore, due to its unique posture stability control, the robot is able to maintain its balance despite unexpected complications such as uneven ground surfaces. As a part of its integrated functions, this robot is able to move on a planned path autonomously and to perform simple operations via wireless teleoperation.

Is imitation learning the route to humanoid robots

Abstract: This review investigates two recent developments in artificial intelligence and neural computation: learning from imitation and the development of humanoid robots. It is postulated that the study of imitation learning offers a promising route to gain new insights into mechanisms of perceptual motor control that could ultimately lead to the creation of autonomous humanoid robots. Imitation learning focuses on three important issues: efficient motor learning, the connection between action and perception, and modular motor control in the form of movement primitives. It is reviewed here how research on representations of, and functional connections between, action and perception have contributed to our understanding of motor acts of other beings. The recent discovery that some areas in the primate brain are active during both movement perception and execution has provided a hypothetical neural basis of imitation. Computational approaches to imitation learning are also described, initially from the perspective of traditional AI and robotics, but also from the perspective of neural network models and statistical-learning research. Parallels and differences between biological and computational approaches to imitation are highlighted and an overview of current projects that actually employ imitation learning for humanoid robots is given.

Emotion and sociable humanoid robots

Abstract: This paper focuses on the role of emotion and expressive behavior in regulating social interaction between humans and expressive anthropomorphic robots, either in communicative or teaching scenarios. We present the scientific basis underlying our humanoid robot's emotion models and expressive behavior, and then show how these scientific viewpoints have been adapted to the current implementation. Our robot is also able to recognize affective intent through tone of voice, the implementation of which is inspired by the scientific findings of the developmental psycholinguistics community. We first evaluate the robot's expressive displays in isolation. Next, we evaluate the robot's overall emotive behavior (i.e. the coordination of the affective recognition system, the emotion and motivation systems, and the expression system) as it socially engages nave human subjects face-to-face.