Adaptive Cost Function for Pointcloud Registration

TL;DR

This paper presents an adaptive cost function for pointcloud registration that automatically estimates sensor noise, leading to improved accuracy and robustness across various sensors and environments.

Contribution

The paper introduces a novel adaptive cost function that dynamically estimates sensor noise for better pointcloud registration performance.

Findings

Significant accuracy improvements over existing methods

Enhanced robustness across diverse sensors and environments

Effective noise estimation in real and synthetic data

Abstract

In this paper we introduce an adaptive cost function for pointcloud registration. The algorithm automatically estimates the sensor noise, which is important for generalization across different sensors and environments. Through experiments on real and synthetic data, we show significant improvements in accuracy and robustness over state-of-the-art solutions.