Depth Estimation for Autonomous Robot Navigation: A Comparative Approach
Depth Estimation for Autonomous Robot Navigation: A Comparative Approach
Depth estimation has long been a fundamental problem both in robotics science and in computer vision. Various methods have been developed and implemented in a large number of applications. Despite the rapid progress in the field the last few years, computation remains a significant issue of the methods employed. In this work, we have implemented two different strategies for inferring depth, both of which are computationally efficient. The first one is inspired by biology, that is optical flow, while the second one is based on a least squares method. In the first strategy, we observe the length variation of the optic flow vectors of a landmark at varying distances and velocities. In the second strategy, we take snapshots of a landmark from different positions and use a least squares approach to estimate the distance between the robot and a landmark. An evaluation of the two different strategies for various depth estimations has been deployed and the results are presented in this paper.
Diamantas, Sotirios
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Oikonomidis, Anastasios
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Crowder, Richard
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Diamantas, Sotirios
569b0bb8-9d90-447c-8a23-16d38f29444f
Oikonomidis, Anastasios
876dbe2e-cc0e-4620-a72b-2b44ccf32a07
Crowder, Richard
ddeb646d-cc9e-487b-bd84-e1726d3ac023
Diamantas, Sotirios, Oikonomidis, Anastasios and Crowder, Richard
(2010)
Depth Estimation for Autonomous Robot Navigation: A Comparative Approach.
IEEE International Conference on Imaging Systems and Techniques, Thessaloniki, Greece.
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Abstract
Depth estimation has long been a fundamental problem both in robotics science and in computer vision. Various methods have been developed and implemented in a large number of applications. Despite the rapid progress in the field the last few years, computation remains a significant issue of the methods employed. In this work, we have implemented two different strategies for inferring depth, both of which are computationally efficient. The first one is inspired by biology, that is optical flow, while the second one is based on a least squares method. In the first strategy, we observe the length variation of the optic flow vectors of a landmark at varying distances and velocities. In the second strategy, we take snapshots of a landmark from different positions and use a least squares approach to estimate the distance between the robot and a landmark. An evaluation of the two different strategies for various depth estimations has been deployed and the results are presented in this paper.
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IEEE_IST2010_finalPaper.pdf
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Submitted date: 1 July 2010
Additional Information:
Event Dates: July, 2010
Venue - Dates:
IEEE International Conference on Imaging Systems and Techniques, Thessaloniki, Greece, 2010-07-01
Organisations:
Agents, Interactions & Complexity
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Local EPrints ID: 268767
URI: http://eprints.soton.ac.uk/id/eprint/268767
PURE UUID: 62547fec-bc69-407c-b518-e6e893e59014
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Date deposited: 19 Mar 2010 22:14
Last modified: 14 Mar 2024 09:15
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Contributors
Author:
Sotirios Diamantas
Author:
Anastasios Oikonomidis
Author:
Richard Crowder
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