Prediction of ICP Pose Uncertainties Using Monte Carlo Simulation with Synthetic Depth Images

Publikation: Kapitel i bog/rapport/konference-proceedingKonferencebidrag i proceedingsForskningpeer review

Abstrakt

In robotics, vision sensors are used to estimate the poses of objects in the environment. However, it is a fundamental problem that the estimated poses are not always accurate enough for a given robotic task. Proper sensor placement can mitigate this problem. We present a method which can predict the pose uncertainties in the Iterative Closest Point (ICP) algorithm, which is often used as the last critical pose refinement step in a pose estimation system. With our method we thus provide a crucial tool needed for the optimization of a robust pose estimation system. Our method relies on the generation of synthetic depth images in a Monte Carlo simulation. In this paper we demonstrate our method for depth sensors which rely on Kinect v1 like technology. We evaluate our method using real depth sensor recordings from the publicly available BigBird dataset. The evaluation shows that the uncertainty predictions of our method are in better correspondence with real world experimental results than the state of the art analytical method.
OriginalsprogEngelsk
TitelProceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
ForlagIEEE
Publikationsdato2017
Sider4640-4647
ISBN (Trykt)978-1-5386-2683-2
ISBN (Elektronisk)978-1-5386-2682-5, 978-1-5386-2681-8
DOI
StatusUdgivet - 2017
Begivenhed2017 IEEE/RSJ International Conference on Intelligent Robots and Systems - Vancouver, Canada
Varighed: 24. sep. 201728. sep. 2017

Konference

Konference2017 IEEE/RSJ International Conference on Intelligent Robots and Systems
LandCanada
ByVancouver
Periode24/09/201728/09/2017
SponsorAIRA, Amazon, Bosch, Clearpath, et al., Guangdong University of Technology

Fingeraftryk

Dyk ned i forskningsemnerne om 'Prediction of ICP Pose Uncertainties Using Monte Carlo Simulation with Synthetic Depth Images'. Sammen danner de et unikt fingeraftryk.

Citationsformater