scholarly journals Real-time replanning using 3D environment for humanoid robot

2011 ◽  
Author(s):  
Leo Baudouin ◽  
Nicolas Perrin ◽  
Thomas Moulard ◽  
Florent Lamiraux ◽  
Olivier Stasse ◽  
...  
Keyword(s):  
Real Time ◽  
Humanoid Robot ◽  
3D Environment

scholarly journals Soft Biometrics for a Socially Assistive Robotic Platform

2015 ◽  
Vol 6 (1) ◽  
Author(s):  
Pierluigi Carcagnì ◽  
Dario Cazzato ◽  
Marco Del Coco ◽  
Pier Luigi Mazzeo ◽  
Marco Leo ◽  
...  
Keyword(s):  
Real Time ◽  
Humanoid Robot ◽  
Field Of View ◽  
Robotic Platform ◽  
Time System ◽  
Real Time System ◽  
Age And Gender ◽  
Gender And Age ◽  
And Gender ◽  
Assistive Robotic

AbstractIn thiswork, a real-time system able to automatically recognize soft-biometric traits is introduced and used to improve the capability of a humanoid robot to interact with humans. In particular the proposed system is able to estimate gender and age of humans in images acquired from the embedded camera of the robot. This knowledge allows the robot to properly react with customized behaviors related to the gender/age of the interacting individuals. The system is able to handle multiple persons in the same acquired image, recognizing the age and gender of each person in the robot’s field of view. These features make the robot particularly suitable to be used in socially assistive applications.

scholarly journals A Cloud Based Disaster Management System

2020 ◽  
Vol 9 (1) ◽  
pp. 6 ◽  
Author(s):  
Omar Cheikhrouhou ◽  
Anis Koubaa ◽  
Anis Zarrad
Keyword(s):  
Real Time ◽  
Disaster Management ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Wireless Sensor ◽  
Game Engine ◽  
New Paradigm ◽  
Lossy Networks ◽  
Training Environment ◽  
3D Environment

The combination of wireless sensor networks (WSNs) and 3D virtual environments opens a new paradigm for their use in natural disaster management applications. It is important to have a realistic virtual environment based on datasets received from WSNs to prepare a backup rescue scenario with an acceptable response time. This paper describes a complete cloud-based system that collects data from wireless sensor nodes deployed in real environments and then builds a 3D environment in near real-time to reflect the incident detected by sensors (fire, gas leaking, etc.). The system’s purpose is to be used as a training environment for a rescue team to develop various rescue plans before they are applied in real emergency situations. The proposed cloud architecture combines 3D data streaming and sensor data collection to build an efficient network infrastructure that meets the strict network latency requirements for 3D mobile disaster applications. As compared to other existing systems, the proposed system is truly complete. First, it collects data from sensor nodes and then transfers it using an enhanced Routing Protocol for Low-Power and Lossy Networks (RLP). A 3D modular visualizer with a dynamic game engine was also developed in the cloud for near-real time 3D rendering. This is an advantage for highly-complex rendering algorithms and less powerful devices. An Extensible Markup Language (XML) atomic action concept was used to inject 3D scene modifications into the game engine without stopping or restarting the engine. Finally, a multi-objective multiple traveling salesman problem (AHP-MTSP) algorithm is proposed to generate an efficient rescue plan by assigning robots and multiple unmanned aerial vehicles to disaster target locations, while minimizing a set of predefined objectives that depend on the situation. The results demonstrate that immediate feedback obtained from the reconstructed 3D environment can help to investigate what–if scenarios, allowing for the preparation of effective rescue plans with an appropriate management effort.

scholarly journals ORHRO: OPEN Robotics Humanoid RObot - from a mechanical retrofit to a new real time industrial controller based walking robot

2019 ◽  
Vol 22 (sup1) ◽  
pp. S502-S504
Author(s):  
A. Eon ◽  
J. Gastebois ◽  
P. Laguillaumie ◽  
P. Vulliez ◽  
P. Seguin ◽  
...  
Keyword(s):  
Real Time ◽  
Humanoid Robot ◽  
Walking Robot ◽  
Industrial Controller

REAL-TIME GAIT PLANNING FOR THE HUMANOID ROBOT Rh-1 USING THE LOCAL AXIS GAIT ALGORITHM

2009 ◽  
Vol 06 (01) ◽  
pp. 71-91 ◽  
Author(s):  
MARIO ARBULU ◽  
CARLOS BALAGUER
Keyword(s):  
Real Time ◽  
Lie Groups ◽  
Humanoid Robot ◽  
Screw Theory ◽  
Step Length ◽  
Center Of Gravity ◽  
Joint Torque ◽  
Continuous Change ◽  
Motion Generation ◽  
Table Model

This paper presents the 3D foot and center of gravity motion planning for the humanoid robot called the "local axis gait" (LAG) algorithm. It permits walking on different kinds of surfaces, such as planes, ramps or stairs. Furthermore, continuous change of the step length and orientation in real time will be possible, due to the real-time linear dynamics model of the walking pattern of the humanoid. The robot model is based on the cart table formulation for planning the center of gravity (COG) and zero moment point (ZMP) motion. The proposed algorithm takes into account physical robot constraints such as joint angles, angular velocity and torques. Torques are computed by the Lagrange method under screws and Lie groups. The LAG is divided into several stages: computation of the footprints; the decision of the ZMP limits around the footprints; the dynamic humanoid COG motion generation based on the cart table model; and joining the footprints of the swing foot by splines. In this way it is possible to generate each step online, using the desired footprints as input. In order to compute the joint torque limits, the Lagrangian method is used under the Lie groups and screw theory. The paper presents and discusses some successful results on the LAG in the full-size humanoid robot Rh-1 developed in the Roboticslab of University Carlos III of Madrid.

Network-Based Humanoid Robot Remote Interaction with the Actual Situation Fusion Technology

2011 ◽  
Vol 271-273 ◽  
pp. 191-196
Author(s):  
Guo Chen Yu ◽  
Zhi Liang Wang ◽  
Lun Xie ◽  
Jia Ming Xu
Keyword(s):  
Real Time ◽  
Robot Control ◽  
Humanoid Robot ◽  
Rapid Development ◽  
Network Technology ◽  
Fusion Technology ◽  
Robot Interaction ◽  
Control Functions ◽  
Remote Interaction ◽  
Client Program

With the rapid development of network technology, network-based humanoid robot technology will also be open to the development of gradual and orderly progress. This article is based on the C / S architecture, the server responsible for controlling the record of news and information network transit between paragraphs; through remote interaction, real-time client to complete the real humanoid robot control functions. Interoperability between the client, first to sign the server. Server information of all registered users to return to the client process, then the client users will be able to get online users to select the remote robot interaction. .When a user operation, the client program as a virtual robot through the virtual robot laboratory will be displayed in real-time robot control results.

The practical requirements for making a conscious robot

1994 ◽  
Vol 349 (1689) ◽  
pp. 133-146 ◽  
Keyword(s):  
Human Brain ◽  
Real Time ◽  
Humanoid Robot ◽  
Thought Experiments ◽  
Coarse Grained ◽  
Human Beings ◽  
Neural Organization

Arguments about whether a robot could ever be conscious have been conducted up to now in the factually impoverished arena of what is ‘possible in principle’. A team at MIT, of which I am a part, is now embarking on a longterm project to design and build a humanoid robot, Cog, whose cognitive talents will include speech, eye-coordinated manipulation of objects, and a host of self-protective, self-regulatory and self-exploring activities. The aim of the project is not to make a conscious robot, but to make a robot that can interact with human beings in a robust and versatile manner in real time, take care of itself, and tell its designers things about itself that would otherwise be extremely difficult if not impossible to determine by examination. Many of the details of Cog’s ‘neural’ organization will parallel what is known (or presumed known) about their counterparts in the human brain, but the intended realism of Cog as a model is relatively coarse-grained, varying opportunistically as a function of what we think we know, what we think we can build, and what we think doesn’t matter. Much of what we think will of course prove to be mistaken; that is one advantage of real experiments over thought experiments.

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