Follow Pedro! An Infrared-based Person-Follower using Nonlinear Optimization

Pedro Pena; Toffee Albina

Follow Pedro! An Infrared-based Person-Follower using Nonlinear Optimization

Robotics 2019-12-17 v1

Authors: Pedro Pena , Toffee Albina

Abstract

We used ROS2 as a platform to conduct AI research for developing a Follow-Me capability as a proof-of-concept on a wheeled robot, demonstrating that AI research is possible in the ROS2 framework. We developed a complete system that uses perception and navigation components based on a sensor suite of fisheye cameras, lidar, and IMU running on an ARM64 Embedded Linux platform that runs ROS2 natively. The perception package detects AR markers and/or IR beacons to track a person. The tracker uses AI algorithms such as particle filters and nonlinear optimization to extract the SE(3) information of the 2D feature.

Keywords

planetary rover autonomy object detection

Cite

@article{arxiv.1912.06837,
  title  = {Follow Pedro! An Infrared-based Person-Follower using Nonlinear Optimization},
  author = {Pedro Pena and Toffee Albina},
  journal= {arXiv preprint arXiv:1912.06837},
  year   = {2019}
}

Comments

5 pages, 4 figures

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