IEEE Robotics & Automation Magazine - September 2019 - 78

A Reproducible
Approach to
Measurable
Robotics

©ISTOCKPHOTO.COM/CYLONPHOTO

Time-Constrained
Exploration Using
Toposemantic
Spatial Models

R-Article

By Jose Luis Susa Rincon and Stefano Carpin

A

s robots become ubiquitous in our everyday lives,
they are more and more often assigned complex
tasks involving multiple, simultaneous objectives.
Moreover, efficiency, envisioned as the ability
to complete more tasks in a given amount of
time, is becoming increasingly important. At the same
Digital Object Identifier 10.1109/MRA.2019.2923452
Date of publication: 5 September 2019

78

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IEEE ROBOTICS & AUTOMATION MAGAZINE

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SEPTEMBER 2019

time, spurred by progress in machine learning, there is a
tendency to explore novel designs in which robots rely
more on visual sensors and less on traditional sensors like
range finders.
Starting from these premises, the objective of this article is
twofold. First, we revisit the classic exploration problem,
introducing temporal constraints in the task and embracing a
toposemantic spatial representation that includes no metric
attribute. To assess the strengths and weaknesses of the various exploration methods abstracting from the underlying
technical implementation, we perform a set of massive simulations in the Robot Operating System (ROS) using its Gazebo simulation environment. This simulation-based approach
1070-9932/19©2019IEEE


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IEEE Robotics & Automation Magazine - September 2019

Table of Contents for the Digital Edition of IEEE Robotics & Automation Magazine - September 2019

Contents
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IEEE Robotics & Automation Magazine - September 2019 - Cover3
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