A Framework for Depth Estimation and Relative Localization of Ground Robots using Computer Vision

• Type: Article in International Conference Proceedings Book
• Date: 2019

Authors

Rômulo T. Rodrigues (Author) Other; Pedro Miraldo (Author) Other; Dimos V. Dimarogonas (Author) Other; António Pedro Aguiar (Author) FEUP

Conference proceedings International

Title: 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019, Macau, SAR, China, November 3-8, 2019

Pages: 3719-3724

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 1 Citation

Other information

Authenticus ID: P-00R-VZD

DOI: 10.1109/iros40897.2019.8968459

Abstract (EN): The 3D depth estimation and relative pose estimation problem within a decentralized architecture is a challenging problem that arises in missions that require coordination among multiple vision-controlled robots. The depth estimation problem aims at recovering the 3D information of the environment. The relative localization problem consists of estimating the relative pose between two robots, by sensing each other's pose or sharing information about the perceived environment. Most solutions for these problems use a set of discrete data without taking into account the chronological order of the events. This paper builds on recent results on continuous estimation to propose a framework that estimates the depth and relative pose between two non-holonomic vehicles. The basic idea consists in estimating the depth of the points by explicitly considering the dynamics of the camera mounted on a ground robot, and feeding the estimates of 3D points observed by both cameras in a filter that computes the relative pose between the robots. We evaluate the convergence for a set of simulated scenarios and show experimental results validating the proposed framework.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6