scholarly journals Improving Human-Robot Interaction and Control Through Augmented Reality

2018 ◽  
Author(s):  
Levi H. Manring ◽  
John Monroe Pederson ◽  
Dillon Gabriel Potts
Keyword(s):  
Augmented Reality ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
And Control

scholarly journals Augmented Reality for Robotics: A Review

Robotics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 21 ◽  
Author(s):  
Zhanat Makhataeva ◽  
Huseyin Varol
Keyword(s):  
Augmented Reality ◽  
Human Robot Interaction ◽  
Multi Agent Systems ◽  
Planning And Control ◽  
Robot Swarms ◽  
Wearable Robots ◽  
Camera Localization ◽  
Recent Developments ◽  
Multi Agent ◽  
And Control

Augmented reality (AR) is used to enhance the perception of the real world by integrating virtual objects to an image sequence acquired from various camera technologies. Numerous AR applications in robotics have been developed in recent years. The aim of this paper is to provide an overview of AR research in robotics during the five year period from 2015 to 2019. We classified these works in terms of application areas into four categories: (1) Medical robotics: Robot-Assisted surgery (RAS), prosthetics, rehabilitation, and training systems; (2) Motion planning and control: trajectory generation, robot programming, simulation, and manipulation; (3) Human-robot interaction (HRI): teleoperation, collaborative interfaces, wearable robots, haptic interfaces, brain-computer interfaces (BCIs), and gaming; (4) Multi-agent systems: use of visual feedback to remotely control drones, robot swarms, and robots with shared workspace. Recent developments in AR technology are discussed followed by the challenges met in AR due to issues of camera localization, environment mapping, and registration. We explore AR applications in terms of how AR was integrated and which improvements it introduced to corresponding fields of robotics. In addition, we summarize the major limitations of the presented applications in each category. Finally, we conclude our review with future directions of AR research in robotics. The survey covers over 100 research works published over the last five years.

scholarly journals A Brief Review of Neural Networks Based Learning and Control and Their Applications for Robots

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Yiming Jiang ◽  
Chenguang Yang ◽  
Jing Na ◽  
Guang Li ◽  
Yanan Li ◽  
...  
Keyword(s):  
Neural Networks ◽  
Nonlinear Systems ◽  
Human Robot Interaction ◽  
Learning Tools ◽  
Robot Interaction ◽  
Practical Applications ◽  
Powerful Learning ◽  
Wide Range ◽  
Complex Nonlinear Systems ◽  
And Control

As an imitation of the biological nervous systems, neural networks (NNs), which have been characterized as powerful learning tools, are employed in a wide range of applications, such as control of complex nonlinear systems, optimization, system identification, and patterns recognition. This article aims to bring a brief review of the state-of-the-art NNs for the complex nonlinear systems by summarizing recent progress of NNs in both theory and practical applications. Specifically, this survey also reviews a number of NN based robot control algorithms, including NN based manipulator control, NN based human-robot interaction, and NN based cognitive control.

GAIT GENERATION AND OPTIMIZATION USING THE ESTIMATION OF DISTRIBUTION ALGORITHM FOR TEENSIZE HUMANOID SOCCER ROBOT RESr-1

2008 ◽  
Vol 05 (03) ◽  
pp. 437-456 ◽  
Author(s):  
LINGYUN HU ◽  
CHANGJIU ZHOU
Keyword(s):  
Hierarchical Control ◽  
Estimation Of Distribution Algorithm ◽  
Human Robot Interaction ◽  
Cooperative Research ◽  
Soccer Robot ◽  
Robot Interaction ◽  
Planning And Control ◽  
Hierarchical Control Architecture ◽  
Estimation Of Distribution ◽  
And Control

This paper gives an overview of locomotion planning and control of a TeenSize humanoid soccer robot, Robo-Erectus Senior (RESr-1), which has been developed as an experimental platform for human–robot interaction and cooperative research in general and robotics soccer games in particular. The locomotion planning and control, along with an introduction of hierarchical control architecture, vision-based behavior and its application in the Humanoid TeenSize soccer challenge, are elaborated. The Estimation of Distribution Algorithm (EDA) is used in locomotion generation and optimization to achieves dynamically stable walk and a powerful kick. By setting different objective functions, smooth walking and powerful kicking can be generated quickly. RESr-1 made its debut at RoboCup 2007, and got fourth place in the Humanoid TeenSize penalty kick competition. In addition, some experimental results on RESr-1's walking, tracking and kicking are presented.

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