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Advances in Robotics: Modeling, Control and Applications
Title
Advances in Robotics: Modeling, Control and Applications
Editor
Calin Ciufudean and Lino García
Price
USD$139.00
ISBN
978-1-461108-443
Clicks
33277

Chapter 12

Advances in Robotics: Modeling, Control and Applications

Efficient State Spaces and Policy Transfer for Robot Navigation

by Kagan Tumer and Matt Knudson

Viewed: 1114

Abstract

Autonomous mobile robots are critical in many real world applications, ranging from planetary exploration to search and rescue. Indeed, the application domains using such robots are steadily increasing, and as the robots get smaller, navigation policies that operate with reduced computational and memory requirements become critical. In addition, as tasks become more complex, directly developing (in this case evolving) navigation policies for such robots becomes slow at best and impossible at worst. In this chapter, we first present a state/action representation that allows robots to learn good navigation policies, but also allows them to transfer the policy to new and more complex situations. In particular, we show how the evolved policies can transfer to situations with: (i) new tasks (different obstacle and target configurations and densities); (ii) new sets of sensors (different resolution); and (iii) new sensor/actuation noise levels (failures or changes in sensing and/or actuation fidelity). Our results show that in all three cases, policies evolved in simple environments and transferred to more complex situations outperform policies directly evolved in the complex situation both in terms of overall performance (up to 30%) and convergence speed (up to 90%).

Author Details

Kagan Tumer
Oregon State University, USA
Matt Knudson
Carnegie Melon University, USA

Citation

Kagan Tumer and Matt Knudson. Efficient State Spaces and Policy Transfer for Robot Navigation. In Advances in Robotics: Modeling, Control and Applications. ISBN:978-1-461108-443. iConcept Press. 0000.

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