ACM Home Page
Please provide us with feedback. Feedback
Mobile human-robot teaming with environmental tolerance
Full text PdfPdf (2.96 MB)
Source
ACM/IEEE International Conference on Human-Robot Interaction archive
Proceedings of the 4th ACM/IEEE international conference on Human robot interaction table of contents
La Jolla, California, USA
SESSION: Situation awareness, interface design and usability table of contents
Pages 157-164  
Year of Publication: 2009
ISBN:978-1-60558-404-1
Authors
Matthew M. Loper  Brown University, Providence, RI, USA
Nathan P. Koenig  University of Southern California, Los Angeles, CA, USA
Sonia H. Chernova  Carnegie Mellon University, Pittsburgh, PA, USA
Chris V. Jones  iRobot Corporation, Bedford, MA, USA
Odest C. Jenkins  Brown University, Providence, RI, USA
Sponsors
SIGART: ACM Special Interest Group on Artificial Intelligence
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 18,   Downloads (12 Months): 109,   Citation Count: 0
Additional Information:

abstract   references   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1514095.1514124
What is a DOI?

ABSTRACT

We demonstrate that structured light-based depth sensing with standard perception algorithms can enable mobile peer-to-peer interaction between humans and robots. We posit that the use of recent emerging devices for depth-based imaging can enable robot perception of non-verbal cues in human movement in the face of lighting and minor terrain variations. Toward this end, we have developed an integrated robotic system capable of person following and responding to verbal and non-verbal commands under varying lighting conditions and uneven terrain. The feasibility of our system for peer-to-peer HRI is demonstrated through two trials in indoor and outdoor environments.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
H. G. Barrow, J. M. Tenenbaum, R. C. Boles, and H. C. Wolf. Parametric correspondence and chamfer matching: Two new techniques for image matching. In IJCAI, pages 659--663, 1977.
 
2
Cepstral, 2008. http://www.cepstral.com.
 
3
C.-C. Chang and C.-J. Lin. LIBSVM: a library for support vector machines, 2001. Software available at http://www.csie.ntu.edu.tw/ cjlin/libsvm.
 
4
N. Dalal, B. Triggs, and C. Schmid. Human detection using oriented histograms of flow and appearance. In European Conference on Computer Vision, 2006.
5
 
6
A. Haasch, S. Hohenner, S. Huwel, M. Kleinehagenbrock, S. Lang, I. Toptsis, G. Fink, J. Fritsch, B. Wrede, and G. Sagerer. BIRON - the bielefeld robot companion. In Int. Workshop on Advances in Service Robotics, pages 27--32, Stuttgart, Germany, 2004.
 
7
O. Jenkins, G. Gonzalez, and M. Loper. Interactive human pose and action recognition using dynamical motion primitives. International Journal of Humanoid Robotics, 4(2):365--385, Jun 2007.
 
8
W. G. Kennedy, M. Buga jska, M. Marge, W. Adams, P. Fransen, B. R., A. C. D., Schultz, and J. G. Trafton. Spatial representation and reasoning for human-robot collaboration. In Twenty-second National Conference on Artificial Intel ligence (AAAI-07), 2007.
 
9
S. Knoop, S. Vacek, and R. Dillmann. Sensor fusion for 3d human body tracking with an articulated 3d body model. In ICRA 2006: Proceedings 2006 IEEE International Conference on Robotics and Automation, pages 1686--1691, May 2006.
 
10
N. Ko jo, T. Inamura, K. Okada, and M. Inaba. Gesture recognition for humanoids using proto-symbol space. In Humanoid Robots, 2006 6th IEEE-RAS International Conference on, pages 76--81, 2006.
11
 
12
 
13
 
14
O. Rogalla, M. Ehrenmann, R. Zollner, R. Becher, and R. Dillmann. Using gesture and speech control for commanding a robot assistant. In Proceedings. 11th IEEE International Workshop on Robot and Human Interactive Communication, pages 454--459, 2002.
15
 
16
D. Schulz. A probabilistic exemplar approach to combine laser and vision for person tracking. In Proceedings of Robotics: Science and Systems, Philadelphia, USA, August 2006.
 
17
H. Shimizu and T. Piggio. Direction estimation of pedestrian from multiple still images. In Intel ligent Vehicles Symposium, pages 596--600, June 2004.
 
18
C. Sminchisescu and A. Telea. Human pose estimation from silhouettes - a consistent approach using distance level sets. In WSCG International Conference on Computer Graphics,Visualization and Computer Vision, pages 413--420, 2002.
 
19
Sphinx-3, 2008. http://cmusphinx.sourceforge.net.
 
20
R. Stiefelhagen, C. Fugen, R. Gieselmann, H. Holzapfel, K. Nickel, and A. Waibel. Natural human-robot interaction using speech, head pose and gestures. In IEEE/RSJ International Conference Intel ligent Robots and Systems, volume 3, pages 2422--2427, Sendai, Japan, 2004.
 
21
SwissRanger specifications, 2008. http://www.swissranger.ch/main.php.
 
22
 
23

Collaborative Colleagues:
Matthew M. Loper: colleagues
Nathan P. Koenig: colleagues
Sonia H. Chernova: colleagues
Chris V. Jones: colleagues
Odest C. Jenkins: colleagues