Not All Who Wander Are Lost: A Localization-Free System for In-the-Wild Mobile Robot Deployments

For background and additional information, see this page: Wandering for Mobile Robot Deployments

A. Nanavati et al., “Not All Who Wander Are Lost: A Localization-Free System for In-the-Wild Mobile Robot Deployments,” in Proceedings of the 2022 ACM/IEEE International Conference on Human-Robot Interaction (HRI), 2022, pp. 422–431, doi: 10.5555/3523760.3523817.

Abstract

It is difficult to run long-term in-the-wild studies with mobile robots. This is partly because the robots we, as human-robot interaction (HRI) researchers, are interested in deploying prioritize expressivity over navigational capabilities, and making those robots autonomous is often not the focus of our research. One way to address these difficulties is with the Wizard of Oz (WoZ) methodology, where a researcher teleoperates the robot during its deployment. However, the constant attention required for teleoperation limits the duration of WoZ deployments, which in-turn reduces the amount of in-the-wild data we are able to collect. Our key insight is that several types of in-the-wild mobile robot studies can be run without autonomous navigation, using wandering instead. In this paper we present and share code for our wandering robot system, which enabled Kuri, an expressive robot with limited sensor and computational capabilities, to traverse the hallways of a 28,000 ft^2 floor for four days. Our system relies on informed direction selection to avoid obstacles and traverse the space, and periodic human help to charge. After presenting the outcomes from the four-day deployment, we then discuss the benefits of deploying a wandering robot, explore the types of in-the-wild studies that can be run with wandering robots, and share pointers for enabling other robots to wander. Our goal is to add wandering to the toolbox of navigation approaches HRI researchers use, particularly to run in-the-wild deployments with mobile robots.

BibTeX Entry

@inproceedings{nanavati2022wandering,
  author = {Nanavati, Amal and Walker, Nick and Taber, Lee and Mavrogiannis, Christoforos and Takayama, Leila and Cakmak, Maya and Srinivasa, Siddhartha},
  cofirst = {2},
  title = {Not All Who Wander Are Lost: A Localization-Free System for In-the-Wild Mobile Robot Deployments},
  booktitle = {Proceedings of the 2022 ACM/IEEE International Conference on Human-Robot Interaction (HRI)},
  location = {Sapporo, Hokkaido, Japan},
  month = mar,
  year = {2022},
  doi = {10.5555/3523760.3523817},
  pages = {422–431},
  numpages = {10},
  keywords = {wizard of oz, wandering, in-the-wild deployment, robot navigation, robots asking for help},
  series = {HRI '22},
  wwwtype = {conference},
  wwwpdf = {https://hcrlab.cs.washington.edu/assets/pdfs/2022/nanavati2022wandering.pdf},
  wwwcode = {https://github.com/hcrlab/kuri_wandering_robot},
  wwwurl = {https://wandering.nickwalker.us}
}