Stanford
Navigation and Autonomous Vehicles Lab
Navigation and Autonomous Vehicles (NAV) Lab

Multi-Robot Collaborative Localization

Research Question: Can We Take Advantage of Connected and Collaborative Vehicles for Safety? 

The increasing number of autonomous systems, such as self-driving cars and UAVs, opens avenues for cooperation among robots through collaborative sensing and communication opportunities. We aim to leverage the abundant sensing information exchange among cooperating vehicles to improve localization robustness and safety.   For example, a UAV flying above tall buildings will have open sky views with ideal GPS signal reception.  Such a UAV can serve as a pseudo GPS satellite to relay the healthy GPS signals to vehicles near the ground with poor GPS reception and erroneous signal measurements.  We use graph theory and distributed algorithms to achieve more robust and attack-resilient localization solutions.

Research Team: 

  • Sriramya Bhamidipati
  • Timmy Hussain
  • Derek Knowles
  • Greg Lund
  • Adyasha Mohanty
  • Akshay Shetty
  • Alexandros Tzikas
  • Asta Wu

Related Works: 

  • Adyasha Mohanty, Remy Zawislak, Sriramya Bhamidipati, and Grace Gao, Precise Relative Positioning for Tandem Drifting Cars, Proceedings of the Institute of Navigation GNSS+ conference (ION GNSS+ 2021), St. Louis, MO, Sep 2021. [paper] [slides] [video]
  • Derek Knowles and Grace Gao, Euclidean Distance Matrix-­based Rapid Fault Detection and Exclusion, Proceedings of the Institute of Navigation GNSS+ conference (ION GNSS+ 2021), St. Louis, MO, Sep 2021. Best Presentation of the Session Award. [paper] [slides] [video]
  • Akshay Shetty, Timmy Hussain and Grace Gao, Decentralized Connectivity Maintenance for Multi-robot Systems Under Motion and Sensing Uncertainties, Proceedings of the Institute of Navigation GNSS+ conference (ION GNSS+ 2021), St. Louis, MO, Sep 2021. Best Presentation of the Session Award. [paper] [slides] [video]
  • Arthur Chu, Shubhendra Chauhan and Grace Gao, GPS Multi-Receiver Direct Position Estimation for Aerial Applications, IEEE Transactions on Aerospace and Electronic Systems, vol. 56, no. 1, pp. 249 - 262, Feb 2020. doi: 10.1109/TAES.2019.2915393. [paper]

  • Tara Mina, Sriramya Bhamidipati and Grace Gao, GPS Spoofing Detection for the Power Grid Network using a Multi-Receiver Hierarchical Framework Architecture,  Navigation: Journal of the Institute of Navigation, vol. 66, no. 4, pp. 857-875, Dec 2019. doi: 10.1002/navi.341. [paper]

  • Sriramya Bhamidipati and Grace Gao, GPS Multi-Receiver Joint Direct Time Estimation and Spoofer Localization, IEEE Transactions on Aerospace and Electronic Systems, vol. 55, no. 4, pp. 1907-1919, Aug 2019. doi: 10.1109/TAES.2018.2879532. [paper]

  • Sriramya Bhamidipati and Grace Gao, Locating Multiple GPS Jammers Using Networked UAVs, IEEE Transactions on Internet of Things, vol. 6, no. 2, pp. 1816 - 1828, Apr 2019. doi: 10.1109/JIOT.2019.2896262. [paper]
  • ​Sriramya Bhamidipati and Grace Gao, Distributed Cooperative SLAM-based Integrity Monitoring Via a Network of Receivers, Proceedings of the Institute of Navigation GNSS+ conference (ION GNSS+ 2019), Miami, FL, Sep 2019. [paper] [slides]
  • Siddharth Tanwar and Grace Gao, Multi-Epoch Multi-Agent Collaborative Localization Using Grid-based 3DMA GNSS and Inter-Agent Ranging, Proceedings of the Institute of Navigation GNSS+ conference (ION GNSS+ 2019), Miami, FL, Sep 2019. [paper] [slides]
  • Siddharth Tanwar and Grace Gao, Decentralized Collaborative Localization in Urban Environments Using 3D-Mapping-Aided (3DMA) GNSS and Inter-Agent Ranging, Proceedings of the Institute of Navigation GNSS+ conference (ION GNSS+ 2018), Miami, FL, Sep 2018. [paper]
  • Siddharth Tanwar and Grace Gao, Decentralized Collaborative Localization with Deep GPS Coupling for UAVs, Proceedings of the IEEE/ION PLANS conference, Monterey, CA, Apr 2018. [paper]