A PnP Algorithm for Two-Dimensional Pose Estimation

TL;DR

This paper introduces a 2D PnP algorithm tailored for cameras with planar motion, improving accuracy and efficiency over traditional 3D methods by exploiting motion constraints and reducing ambiguity.

Contribution

The paper presents a novel 2D PnP algorithm that leverages planar motion constraints to enhance pose estimation accuracy and computational performance.

Findings

Outperforms existing 3D PnP algorithms in accuracy

Offers faster computation due to reduced search space

Demonstrates robustness to noise in pose estimation

Abstract

We propose a PnP algorithm for a camera constrained to two-dimensional motion (applicable, for instance, to many wheeled robotics platforms). Leveraging this assumption allows accuracy and performance improvements over 3D PnP algorithms due to the reduction in search space dimensionality. It also reduces the incidence of ambiguous pose estimates (as, in most cases, the spurious solutions fall outside the plane of movement). Our algorithm finds an approximate solution by solving a polynomial system and refines its prediction iteratively to minimize the reprojection error. The algorithm compares favorably to existing 3D PnP algorithms in terms of accuracy, performance, and robustness to noise.