UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Sensor Path Planning Using Reinforcement Learning

Folker, H; Ritchie, M; Charlish, A; Griffiths, H; (2020) Sensor Path Planning Using Reinforcement Learning. In: 2020 IEEE 23rd International Conference on Information Fusion (FUSION). IEEE: Rustenburg, South Africa, South Africa. Green open access

[img]
Preview
Text
Ritchie_fusion_2020 (1).pdf - Accepted version

Download (453kB) | Preview

Abstract

Reinforcement learning is the problem of autonomously learning a policy guided only by a reward function. We evaluate the performance of the Proximal Policy Optimization (PPO) reinforcement learning algorithm on a sensor management task and study the influence of several design choices about the network structure and reward function. The chosen sensor management task is optimizing the sensor path to speed up the localization of an emitter using only bearing measurements. Furthermore, we discuss generic advantages and challenges when using reinforcement learning for sensor management.

Type: Proceedings paper
Title: Sensor Path Planning Using Reinforcement Learning
Event: Fusion 2020
Dates: 06 July 2020 - 17 July 2020
Open access status: An open access version is available from UCL Discovery
DOI: 10.23919/FUSION45008.2020.9190242
Publisher version: https://doi.org/10.23919/FUSION45008.2020.9190242
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10105016
Downloads since deposit
34Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item