Locking On: Leveraging Dynamic Vehicle-Imposed Motion Constraints to Improve Visual Localization

by   Stephen Hausler, et al.

Most 6-DoF localization and SLAM systems use static landmarks but ignore dynamic objects because they cannot be usefully incorporated into a typical pipeline. Where dynamic objects have been incorporated, typical approaches have attempted relatively sophisticated identification and localization of these objects, limiting their robustness or general utility. In this research, we propose a middle ground, demonstrated in the context of autonomous vehicles, using dynamic vehicles to provide limited pose constraint information in a 6-DoF frame-by-frame PnP-RANSAC localization pipeline. We refine initial pose estimates with a motion model and propose a method for calculating the predicted quality of future pose estimates, triggered based on whether or not the autonomous vehicle's motion is constrained by the relative frame-to-frame location of dynamic vehicles in the environment. Our approach detects and identifies suitable dynamic vehicles to define these pose constraints to modify a pose filter, resulting in improved recall across a range of localization tolerances from 0.25m to 5m, compared to a state-of-the-art baseline single image PnP method and its vanilla pose filtering. Our constraint detection system is active for approximately 35% of the time on the Ford AV dataset and localization is particularly improved when the constraint detection is active.


page 1

page 7


Simultaneous Localization and Mapping with Dynamic Rigid Objects

Accurate estimation of the environment structure simultaneously with the...

DynaVINS: A Visual-Inertial SLAM for Dynamic Environments

Visual inertial odometry and SLAM algorithms are widely used in various ...

Localization of Autonomous Vehicles: Proof of Concept for A Computer Vision Approach

This paper introduces a visual-based localization method for autonomous ...

Improving Worst Case Visual Localization Coverage via Place-specific Sub-selection in Multi-camera Systems

6-DoF visual localization systems utilize principled approaches rooted i...

Amos-SLAM: An Anti-Dynamics Two-stage SLAM Approach

The traditional Simultaneous Localization And Mapping (SLAM) systems rel...

Leveraging Dynamic Objects for Relative Localization Correction in a Connected Autonomous Vehicle Network

High-accurate localization is crucial for the safety and reliability of ...

Line-Circle: A Geometric Filter for Single Camera Edge-Based Object Detection

This paper presents a state-of-the-art approach in object detection for ...

Please sign up or login with your details

Forgot password? Click here to reset