NDLI: A novel way to implement self-localization in a multi-robot experimental platform

Content Provider	IEEE Xplore Digital Library
Author	Sheng Zhao Kumar, M.
Copyright Year	2010
Description	Author affiliation: Univ. of Cincinnati, Cincinnati, OH, USA (Sheng Zhao; Kumar, M.)
Abstract	Self-localization is an important part of multi-robot experiments. The traditional way to obtain the global pose (position and orientation) of a robot is to attach a unique pattern to the robot. A centralized sensor, such as a camera, is typically used to identify the pattern and estimate its pose directly. However, the pattern-based localization scheme lends itself a poor scalability property because, in presence of a large number of robots, the recognition of all patterns may result into a computational bottleneck. Moreover, the implementation of this technique in a decentralized framework is questionable. Additionally, the practicality of designing a large number of unique patterns and attaching them on often miniature robots present some challenges. To overcome the use of a pattern, a novel method has been proposed in this paper for the robots to obtain their global poses without using any pattern. In this method, we run Extended Kalman Filter (EKF) on each robot to fuse the global position data with the control input data to estimate the orientation. In a multi-robot setting, this becomes challenging because the positional data is untagged and robots do not have a priori knowledge about which data pertains to their own position. To overcome this issue, we propose a method in which each robot can identify its own track from the other's tracks by comparing the average errors over time between prediction and measurement in the EKFs that are run on each candidate trajectory. Therefore, instead of trying to identify robots in a centralized manner for localization, we distribute the task to each robot and let them estimate their pose on their own. Extensive simulations and experiments have been conducted and the results are provided to show the effectiveness of this method.
Starting Page	6834
Ending Page	6839
File Size	2108753
Page Count	6
File Format	PDF
ISBN	9781424474264
ISSN	07431619
e-ISBN	9781424474271
DOI	10.1109/ACC.2010.5531578
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-06-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	American Automatic Control Council(AACC)
Subject Keyword	Robot kinematics Robot sensing systems Orbital robotics Robot vision systems Cameras Pattern recognition Testing Joining processes Scalability Fuses
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Sparse appearance based modeling for robot localization

Multi Robot Object Tracking and Self Localization Using Visual Percept Relations

Topological robot localization by training a vision-based transition detector

Heterogeneous Multi-Robot Localization in Unknown 3D Space

VideoTrek: A vision system for a tag-along robot

The vision-based metric self-localization of indoor mobile robot using projective geometry

Positional estimation of a mobile robot using edge visibility regions

Toward a scalable modular robotic system

Robot localization using uncalibrated camera invariants

A novel way to implement self-localization in a multi-robot experimental platform

Similar Documents

Sparse appearance based modeling for robot localization

Multi Robot Object Tracking and Self Localization Using Visual Percept Relations

Topological robot localization by training a vision-based transition detector

Heterogeneous Multi-Robot Localization in Unknown 3D Space

VideoTrek: A vision system for a tag-along robot

The vision-based metric self-localization of indoor mobile robot using projective geometry

Positional estimation of a mobile robot using edge visibility regions

Toward a scalable modular robotic system

Robot localization using uncalibrated camera invariants

A novel way to implement self-localization in a multi-robot experimental platform