STALKERBOT : learning to navigate dynamic human environments by following people

Murphy, Elizabeth & Corke, Peter (2012) STALKERBOT : learning to navigate dynamic human environments by following people. In Carnegie, Dale (Ed.) Proceedings of the 2012 Australasian Conference on Robotics & Automation, Australian Robotics & Automation Association, Wellington, New Zealand.

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Abstract

Service robots that operate in human environments will accomplish tasks most efficiently and least disruptively if they have the capability to mimic and understand the motion patterns of the people in their workspace. This work demonstrates how a robot can create a humancentric navigational map online, and that this map re ects changes in the environment that trigger altered motion patterns of people. An RGBD sensor mounted on the robot is used to detect and track people moving through the environment. The trajectories are clustered online and organised into a tree-like probabilistic data structure which can be used to detect anomalous trajectories. A costmap is reverse engineered from the clustered trajectories that can then inform the robot's onboard planning process. Results show that the resultant paths taken by the robot mimic expected human behaviour and can allow the robot to respond to altered human motion behaviours in the environment.

Impact and interest:

1 citations in Scopus
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ID Code: 57792
Item Type: Conference Paper
Refereed: Yes
Keywords: Service robots, Navigation
ISBN: 978-0-9807404-3-1
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Control Systems Robotics and Automation (090602)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2012 Consult the authors
Deposited On: 06 Mar 2013 00:28
Last Modified: 12 Jun 2013 15:34

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