Name
Abstract | ||
|---|---|---|
This abstract outlines the algorithms and robot hardware used in the UBC robot competing in the Semantic Robot Vision Challenge (SRVC), held at the AAAI'07 conference in Vancouver, Canada. Successfully completing the SRVC involves smooth integration of tasks such as data acquisition, training, obstacle avoidance, visual search, and object recognition. Given that these tasks spanseveral research disciplines, successful integration is a formidable task. The value of working on these problems jointly isthat assumptions built into an isolated method will be exposed whenit is integrated, thus highlighting where further research is required. In addition, this will focus research on robots that can navigate safely and identify objects in their environment. |
Year | Venue | Keywords |
|---|---|---|
2007 | AAAI | ubc semantic robot vision |
Field | DocType | Citations |
Obstacle avoidance,Computer vision,Visual search,Robot vision,Computer science,Data acquisition,Human–computer interaction,Artificial intelligence,Robot vision systems,Robot,Machine learning,Cognitive neuroscience of visual object recognition | Conference | 0 |
PageRank | References | Authors |
0.34 | 18 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Scott Helmer | 1 | 176 | 11.49 |
| David Meger | 2 | 403 | 32.90 |
| Per-Erik Forssén | 3 | 391 | 25.70 |
| Tristram Southey | 4 | 154 | 7.61 |
| Sancho McCann | 5 | 200 | 7.28 |
| Pooyan Fazli | 6 | 56 | 7.04 |
| James J. Little | 7 | 2430 | 269.59 |
| D. G. Lowe | 8 | 15718 | 1413.60 |