Name
Abstract | ||
|---|---|---|
A method for behavior acquisition that considers embodiment by associating tactile information to visual input is described. An agent that acts in the physical world always suffers constraints derived from embodiment. On the other hand, embodiment plays a very important role in the formation of visual function. Philosophical and clinical medicine findings assert that vision does not function without learning through experiences of haptic motion. In this paper, we discuss the relation between vision, embodiment, and behavior. We develop a method for behavior acquisition through associating vision and tactile sensors. We perform experiments of obstacle avoidance using a computer simulation and a real agent to test the validity of our method. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1109/IRDS.2002.1041515 | Intelligent Robots and Systems, 2002. IEEE/RSJ International Conference |
Keywords | Field | DocType |
collision avoidance,mobile agents,mobile robots,robot vision,tactile sensors,unsupervised learning,Markov decision problem,behavior acquisition method,computer simulation,embodiment,haptic motion,learning through experience,obstacle avoidance,real agent,tactile information,vision-based agent,visual input | Obstacle avoidance,Computer vision,Robot vision,Computer science,Vision based,Unsupervised learning,Artificial intelligence,Markov decision problem,Haptic technology,Mobile robot,Tactile sensor | Conference |
Volume | Citations | PageRank |
1 | 0 | 0.34 |
References | Authors | |
3 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kazunori Terada | 1 | 73 | 17.42 |
| Takayuki Nakamura | 2 | 22 | 4.97 |
| Hideaki Takeda | 3 | 179 | 25.16 |