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Follow a Human using a Mobile Robot Regardless of the Walking Speed
Conference proceeding

Follow a Human using a Mobile Robot Regardless of the Walking Speed

Thiruketheeswaran Shaganan, Ran Liu, Chau Yuen, Sumudu Hasala Marakkalage, Madhushanka Padmal, U-Xuan Tan and U-Xuan Calvin Tan
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Conference Proceedings, p.351
01/01/2018

Abstract

Algorithms Human motion Inertial sensing devices Mechatronics Odometers Robotics Robots Walking
Conference Title: 2018 3rd International Conference on Advanced Robotics and Mechatronics (ICARM) Conference Start Date: 2018, July 18 Conference End Date: 2018, July 20 Conference Location: Singapore city, Singapore The humanity is ready to merge intelligent robots into their habitual circumstances to work together, share feelings, and make self-reliant compliance. The capability to follow a human autonomously is essential for a mobile robot to interact with humans. Existing work either requires the human to be in line-of-sight or needs a beacon to be installed, which has great constraints on the human mobility. In this paper, we propose an approach to allow a mobile robot to follow a human regardless of his walking speed. In our setup, a human carries a Tango phone that can perform motion tracking using visual inertial sensing and create a map using its RGB-D sensor. The robot localizes itself in the map by incorporating its on-board Kinect and odometry information. The map quality decreases exponentially with increasing human speed. To produce a map that is suitable for the localization and navigation of the mobile robot, we, therefore, propose a map filter algorithm to improve the map quality. Instead of just following the human path, we propose an algorithm (i.e., trajectory filter) to reduce the cost of path and follow the human simultaneously. Experiments are conducted and the capability is illustrated using ROS on a turletbot platform. We also provide a video link to demonstrate our approach at 202. 94. 70. 33/videos/icarm2018. mp4.

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