Humanizing NAO robot teleoperation using ROS

Rodriguez, Igor; Astigarraga, Aitzol; Jauregi, E.; Ruiz, Txelo; Lazkano, Elena

doi:10.1109/humanoids.2014.7041357

Cited by 31 publications

(14 citation statements)

References 12 publications

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“…During calibration a complex reference coordination between Kinect and robot coordinate frames requires a lot of code and skills that therapists or educators do not have. Often the operator stays at predefined area in front of the Kinect view [7] or complex transformation matrices are used for calibration between Kinect and NAO coordinate systems since different areas of the input space require different compensations and scale independence.…”

Section: Existing Solutionsmentioning

confidence: 99%

Wireless Kinect-NAO Framework Based on Takagi-Sugeno Fuzzy Inference System

Lekova¹,

Krastev²,

Chavdarov³

2017

Information Technologies and Control

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In the context of learning new skills by imitation for children with special educational needs, we propose Wireless Kinect-NAO Framework (WKNF) for robot teleoperation in real time based on Takagi-Sugeno (T-S) Fuzzy Inference System. The new solutions here are related to complex whole-body motion retargeting, standing body stabilization, view invariance and smoothness of robot motions. The raw depth Kinect data are fuzzified and processed by median filter. The joint angles estimation for motion mapping of Human to NAO movements is based on fuzzy logic and featured angles rather than direct angles are calculated by Inverse Kinematics due to differences in the human and robot kinematics. During the joint angles calculation nonlinearities are observed as a result of ambiguity of Kinect 3D joint coordinates in different offsets. NAO kinematic limitations and nonlinearities in workspace are decomposed and linearly approximated by T-S fuzzy rules of zero and first order that have local support in 2D projections. To prevent the robot to fall down, the center of mass is considered in order NAO to stay within a support and safe polygon. The feasibility of the proposed framework has been proven by real experiments.

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Section: Existing Solutionsmentioning

confidence: 99%

Wireless Kinect-NAO Framework Based on Takagi-Sugeno Fuzzy Inference System

Lekova¹,

Krastev²,

Chavdarov³

2017

Information Technologies and Control

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“…The robot was required to give some explanations about itself, and to produce a verse given the rhymes. The robot was teleoperated by human gestures captured by a Kinect sensor (see [27]); NAO gesticulated while chatting, and moved around the stage according to the teleoperator commands (video available at [25]). Fig.…”

Section: Body Language Developmentmentioning

confidence: 99%

Singing minstrel robots, a means for improving social behaviors

Rodriguez

Astigarraga

Ruiz

et al. 2016

2016 IEEE International Conference on Robotics and Automation (ICRA)

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Bertsolaritza, Basque improvised contest poetry, offers another sphere to develop robot body language and robot communication capabilities, that shares some similarities with theatrical performances. It is also a new area to work on social robotics. The work presented in this paper makes some steps forward in designing and implementing the set of behaviors the robots need to show in the stage to increase, on the one hand robot autonomy and on the other hand, credibility and sociability.

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“…A real-time human imitation system based on non-invasive image processing techniques has been proposed in [3], but authors use input coming from RGBD images. A Microsoft Kinect has been used as optical motion capture sensor for arm control in [22,27]. Head pose angles have been estimated using the Kinect for a teleoperation scenario for the Furhat robot head in [28], while a learning scenarios for people with autism spectrum disorder has been proposed in [29].…”

Section: Introductionmentioning

confidence: 99%

Real-Time Human Head Imitation for Humanoid Robots

Cazzato

Cimarelli

Sánchez-López

et al. 2019

Proceedings of the 2019 3rd International Conference on Artificial Intelligence and Virtual Reality

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The ability of the robots to imitate human movements has been an active research study since the dawn of the robotics. Obtaining a realistic imitation is essential in terms of perceived quality in human-robot interaction, but it is still a challenge due to the lack of effective mapping between human movements and the degrees of freedom of robotics systems. If high-level programming interfaces, software and simulation tools simplified robot programming, there is still a strong gap between robot control and natural user interfaces. In this paper, a system to reproduce on a robot the head movements of a user in the field of view of a consumer camera is presented. The system recognizes the presence of a user and its head pose in real-time by using a deep neural network, in order to extract head position angles and to command the robot head movements consequently, obtaining a realistic imitation. At the same time, the system represents a natural user interface to control the Aldebaran NAO and Pepper humanoid robots with the head movements, with applications in human-robot interaction. CCS Concepts • Human-centered Computing ➝ Human computer interaction (HCI) • Computer systems organization → Embedded and cyber-physical systems → Robotics

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Humanizing NAO robot teleoperation using ROS

Cited by 31 publications

References 12 publications

Wireless Kinect-NAO Framework Based on Takagi-Sugeno Fuzzy Inference System

Wireless Kinect-NAO Framework Based on Takagi-Sugeno Fuzzy Inference System

Singing minstrel robots, a means for improving social behaviors

Real-Time Human Head Imitation for Humanoid Robots

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