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Vision-Based Behavior Acquisition For A Shooting Robot By Using A Reinforcement Learning
| Content Provider | Semantic Scholar |
|---|---|
| Author | Asada, Minoru Noda, Shoichi Tawaratsumida, Sukoya Hosoda, Koh |
| Copyright Year | 1994 |
| Abstract | We propose a method which acquires a purposive behavior for a mobile robot to shoot a ball into the goal by using a vision-based reinforcement learning. A mobile robot (an agent) does not need to know any parameters of the 3-D environment or its kinematics/dynamics. Information about the changes of the environment is only the image captured from a single TV camera mounted on the robot. An action-value function in terms of state is to be learned. Image positions of a ball and a goal are used as a state variable which shows the effect of an action previously taken. After the learning process, the robot tries to carry a ball near the goal and to shoot it. Both computer simulation and real robot experiments are shown, and discussion on the role of vision in the context of the vision-based reinforcement learning is given. |
| Starting Page | 112 |
| Ending Page | 118 |
| Page Count | 7 |
| File Format | PDF HTM / HTML |
| DOI | 10.1109/VL.1994.365601 |
| Volume Number | 93 |
| Alternate Webpage(s) | http://www.er.ams.eng.osaka-u.ac.jp/Paper/1994/Asada94b.pdf |
| Alternate Webpage(s) | https://doi.org/10.1109/VL.1994.365601 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
