Abstract
In this research we propose a model of autonomous robot that is able to survive in real world outdoor environment without human intervention. For an autonomous robot, energy is a very important factor, so it is only natural that the ability of the robot to accumulate energy should be used as evaluation of the robot's survival strategy. The robot in this study is equipped with a solar panel, and a model of neural network ensemble. The solar panel enables the robot to autonomously accumulate energy in the outdoor environment, while the neural network ensemble enables the robot to acquire strategies that are needed in order to survive in the environment. The accumulated energy is considered as the feedback from the environment to measure the efficiency of the strategy exerted by the robot, and used as learning guidance for the robot to survive.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - IEEE International Conference on Robotics and Automation |
| Pages | 3571-3575 |
| Number of pages | 5 |
| Volume | 3 |
| Publication status | Published - 2003 |
| Event | 2003 IEEE International Conference on Robotics and Automation - Taipei, Taiwan, Province of China Duration: 2003 Sep 14 → 2003 Sep 19 |
Other
| Other | 2003 IEEE International Conference on Robotics and Automation |
|---|---|
| Country | Taiwan, Province of China |
| City | Taipei |
| Period | 03/9/14 → 03/9/19 |
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ASJC Scopus subject areas
- Software
- Control and Systems Engineering
Cite this
Strategy acquirement by survival robots in outdoor environment. / Hartono, Pitoyo; Tabe, Keishiro; Suzuki, Kenji; Hashimoto, Shuji.
Proceedings - IEEE International Conference on Robotics and Automation. Vol. 3 2003. p. 3571-3575.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Strategy acquirement by survival robots in outdoor environment
AU - Hartono, Pitoyo
AU - Tabe, Keishiro
AU - Suzuki, Kenji
AU - Hashimoto, Shuji
PY - 2003
Y1 - 2003
N2 - In this research we propose a model of autonomous robot that is able to survive in real world outdoor environment without human intervention. For an autonomous robot, energy is a very important factor, so it is only natural that the ability of the robot to accumulate energy should be used as evaluation of the robot's survival strategy. The robot in this study is equipped with a solar panel, and a model of neural network ensemble. The solar panel enables the robot to autonomously accumulate energy in the outdoor environment, while the neural network ensemble enables the robot to acquire strategies that are needed in order to survive in the environment. The accumulated energy is considered as the feedback from the environment to measure the efficiency of the strategy exerted by the robot, and used as learning guidance for the robot to survive.
AB - In this research we propose a model of autonomous robot that is able to survive in real world outdoor environment without human intervention. For an autonomous robot, energy is a very important factor, so it is only natural that the ability of the robot to accumulate energy should be used as evaluation of the robot's survival strategy. The robot in this study is equipped with a solar panel, and a model of neural network ensemble. The solar panel enables the robot to autonomously accumulate energy in the outdoor environment, while the neural network ensemble enables the robot to acquire strategies that are needed in order to survive in the environment. The accumulated energy is considered as the feedback from the environment to measure the efficiency of the strategy exerted by the robot, and used as learning guidance for the robot to survive.
UR - http://www.scopus.com/inward/record.url?scp=0344033784&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0344033784&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:0344033784
VL - 3
SP - 3571
EP - 3575
BT - Proceedings - IEEE International Conference on Robotics and Automation
ER -