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Multi-robot Human Guidance using Topological Graphs.
Piyush Khandelwal
and Peter Stone.
In AAAI Spring 2014 Symposium on Qualitative Representations
for Robots (AAAI-SSS), March 2014.
Prior approaches to human guidance using robots inside a building have typically been limited to a single robot guide that navigates a human from start to goal. However, due to their limited mobility, the robot is often unable to keep up with the human's natural speed. In contrast, this paper addresses this difference in mobility between robots and people by presenting an approach that uses multiple robots to guide a human. Our approach uses a compact topological graph representation of the environment, and we first present the procedure for generating this representation. Next, we formulate the multi-robot guidance problem as a Markov Decision Process (MDP). Using a model of human motion in the presence of guiding robots, we define the transition function for this MDP. Finally, we solve the MDP using Value Iteration to obtain an optimal policy for placing robots and evaluate this policy's effectiveness.
@InProceedings{AAAISSS14-khandelwal,
author = {Piyush Khandelwal and Peter Stone},
title = {Multi-robot Human Guidance using Topological Graphs},
booktitle = {AAAI Spring 2014 Symposium on Qualitative Representations for Robots (AAAI-SSS)},
location = {Stanford, California, USA},
month = {March},
year = {2014},
abstract = {
Prior approaches to human guidance using robots inside a building have
typically been limited to a single robot guide that navigates a human
from start to goal. However, due to their limited mobility, the robot is
often unable to keep up with the human's natural speed. In contrast, this
paper addresses this difference in mobility between robots and people by
presenting an approach that uses multiple robots to guide a human. Our
approach uses a compact topological graph representation of the
environment, and we first present the procedure for generating this
representation. Next, we formulate the multi-robot guidance problem as a
Markov Decision Process (MDP). Using a model of human motion in the
presence of guiding robots, we define the transition function for this
MDP. Finally, we solve the MDP using Value Iteration to obtain an
optimal policy for placing robots and evaluate this policy's
effectiveness.
},
}
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