ICRA 2011 Paper Abstract

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Paper TuA112.3

Aragues, Rosario (Universidad de Zaragoza, DIIS-I3A), Carlone, Luca (Politecnico di Torino), Calafiore, Giuseppe (Politecnico di Torino), Sagues, Carlos (University of Zaragoza)

Multi Agent Localization from Noisy Relative Pose Measurements

Scheduled for presentation during the Regular Sessions "Distributed Robot Systems I" (TuA112), Tuesday, May 10, 2011, 08:50−09:05, Room 5H

2011 IEEE International Conference on Robotics and Automation, May 9-13, 2011, Shanghai International Conference Center, Shanghai, China

This information is tentative and subject to change. Compiled on March 30, 2020

Keywords Distributed Robot Systems, Localization, Sensor Networks

Abstract

In this paper we address the problem of estimating the poses of a team of agents when they do not share any common reference frame. Each agent is capable of measuring the relative position and orientation of its neighboring agents, however these measurements are not exact but they are corrupted with noises. The goal is to compute the pose of each agent relative to an anchor node. We present a strategy where, first of all, the agents compute their orientations relative to the anchor. After that, they update the relative position measurements according to these orientations, to finally compute their positions. As contribution we discuss the proposed strategy, that has the interesting property that can be executed in a distributed fashion. The distributed implementation allows each agent to recover its pose using exclusively local information and local interactions with its neighbors. This algorithm has a low memory load, since it only requires each node to maintain an estimate of its own orientation and position.

 

 

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