Robot Head Motion Control with an Emphasis on Realism of Neck---Eye Coordination during Object Tracking

Authors:
Jartuwat Rajruangrabin;Dan O. Popa
Affiliations:
Automation & Robotics Research Institute, The University of Texas, Arlington, USA;Automation & Robotics Research Institute, The University of Texas, Arlington, USA
Venue:
Journal of Intelligent and Robotic Systems
Year:
2011

Citing 3
Cited 4

Introduction to Reinforcement Learning

Introduction to Reinforcement Learning
Challenges in building robots that imitate people

Imitation in animals and artifacts
Active vision for sociable robots

IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans

Enhanced therapeutic interactivity using social robot Zeno

Proceedings of the 4th International Conference on PErvasive Technologies Related to Assistive Environments
Implementation of interactive arm playback behaviors of social robot Zeno for autism spectrum disorder therapy

Proceedings of the 5th International Conference on PErvasive Technologies Related to Assistive Environments
RoDiCA: a human-robot interaction system for treatment of childhood autism spectrum disorders

Proceedings of the 5th International Conference on PErvasive Technologies Related to Assistive Environments
A biologically constrained architecture for developmental learning of eye---head gaze control on a humanoid robot

Autonomous Robots

Quantified Score

Hi-index	0.00

Visualization

Abstract

Important aspects of present-day humanoid robot research is to make such robots look realistic and human-like, both in appearance, as well as in motion and mannerism. In this paper, we focus our study on advanced control leading to realistic motion coordination for a humanoid's robot neck and eyes while tracking an object. The motivating application for such controls is conversational robotics, in which a robot head "actor" should be able to detect and make eye contact with a human subject. Therefore, in such a scenario, the 3D position and orientation of an object of interest in space should be tracked by the redundant head---eye mechanism partly through its neck, and partly through its eyes. In this paper, we propose an optimization approach, combined with a real-time visual feedback to generate the realistic robot motion and robustify it. We also offer experimental results showing that the neck---eye motion obtained from the proposed algorithm is realistic comparing to the head---eye motion of humans.