Mobile human-robot teaming with environmental tolerance

• Published in: 2009 4th ACM/IEEE International Conference on Human-Robot Interaction (HRI) pp. 157 - 164
• Main Authors: Loper, Matthew M., Koenig, Nathan P., Chernova, Sonia H., Jones, Chris V., Jenkins, Odest C.
• Format: Conference Proceeding
• Language: English
• Published: New York, NY, USA ACM 09.03.2009; IEEE
• Series: ACM Conferences
• Subjects: Cameras; Computer systems organization > Embedded and cyber-physical systems > Robotics > External interfaces for robotics; Computing methodologies > Artificial intelligence > Computer vision; Computing methodologies > Artificial intelligence > Computer vision > Computer vision problems; Computing methodologies > Artificial intelligence > Computer vision > Computer vision problems > Tracking; Computing methodologies > Artificial intelligence > Computer vision > Computer vision tasks > Scene understanding; gesture recognition; Hidden Markov models; Human-robot interaction; Humans; person following; Robot vision systems; Speech recognition; person following; human-robot interaction; gesture recognition
• ISBN: 1605584045; 9781605584041
• ISSN: 2167-2121
• DOI: 10.1145/1514095.1514124

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.