Full Content is available to subscribers

Subscribe/Learn More  >

Developing Moving Horizon Estimation Based Ranging Measurement for Supporting Vision-Aided Inertial Navigation System

[+] Author Affiliations
Trung Nguyen, George K. I. Mann, Andrew Vardy, Raymond G. Gosine

Memorial University of Newfoundland, St. John’s, NL, Canada

Paper No. DSCC2017-5185, pp. V002T17A006; 9 pages
  • ASME 2017 Dynamic Systems and Control Conference
  • Volume 2: Mechatronics; Estimation and Identification; Uncertain Systems and Robustness; Path Planning and Motion Control; Tracking Control Systems; Multi-Agent and Networked Systems; Manufacturing; Intelligent Transportation and Vehicles; Sensors and Actuators; Diagnostics and Detection; Unmanned, Ground and Surface Robotics; Motion and Vibration Control Applications
  • Tysons, Virginia, USA, October 11–13, 2017
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-5828-8
  • Copyright © 2017 by ASME


The objective of this paper is to develop an advanced Vision-and-Ranging-aided Inertial Navigation System (VRINS), which combines a Vision-aided Inertial Navigation System (VINS) with Moving Horizon Estimation (MHE) based ranging measurement update. The traditional VINS estimate suffers the error accumulation from the camera observation, which makes the system diverge and fails to track the vehicle trajectory in long-term operation. Hence, a ranging sensor is integrated with VINS in the sequential-sensor-update structure, which allows the filter to operate for longer duration. The ranging measurement update is developed with the MHE, which directly incorporates the system constraints into the optimization process. The VINS is developed with Cubature Multi-State Constraint Kalman Filter (MSCKF), which has 30-dimension filter state, tight constraints of state transition and observability. Those elements need to be considered in the design of MHE optimization. The implementation of MHE is conducted with CASADI library. The proposed VRINS will be validated using KITTI dataset and compared against the VINS.

Copyright © 2017 by ASME
Topics: Navigation



Interactive Graphics


Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature

Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal

Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In