Name
Abstract | ||
|---|---|---|
Our study is concerned with avoiding the local minimum that occurs when the mobile robot is trapped at a concave-shaped obstacle. Mobile robots use VFF (Virtual Force Field) as their autonomous navigation method. This algorithm generates the attractive force from the target and the repulsive force from the obstacle. So using the sum of these forces, the mobile robot moves to the target point. The method to avoid a local minimum has two steps. The first step is that the mobile robot detects being trapped by an obstacle. The second step is that the mobile robot escapes from the trap point. Then the mobile robot can move to the target point. To execute this, our study uses a grid map to represent the robotpsilas surroundings. The map is constructed by the robot sensor. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/MFI.2008.4648095 | MFI |
Field | DocType | ISBN |
Obstacle,Computer vision,Grid reference,Distance measurement,Computer science,Robot kinematics,Artificial intelligence,Mobile robot navigation,Robot,Mobile robot | Conference | 978-1-4244-2144-2 |
Citations | PageRank | References |
1 | 0.36 | 6 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Soonmook Jeong | 1 | 24 | 3.42 |
| Tae Houn Song | 2 | 7 | 3.40 |
| Ji hwan Park | 3 | 19 | 7.05 |
| Jae Wook Jeon | 4 | 565 | 77.35 |