Name
Abstract | ||
|---|---|---|
There are many kinds of sensors equipped on the robot gripper, for example, force sensor, proximity sensor, displacement sensor and etc. They can all be utilized to determine the state of connection. However, due to measurement error, uncertain work environment, no data of any certain sensor is sufficient to determine the state of connection. In order to grasp objects safely and reliably, the information fusion should be carried out for the output data of multi-sensors. In this paper, we present a novel technique to do the feature-level data fusion by RBF network. According to the result of fusion, control system can fast and accurately determine the state of connection between gripper and objects in real-time. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/CSO.2009.331 | CSO (1) |
Keywords | Field | DocType |
certain sensor,force sensor,output data,control system,rbf network,proximity sensor,robot gripper,robotic multi-sensor gripper,displacement sensor,feature-level data fusion,information fusion,force,sensor fusion,measurement error,data fusion,real time,measurement errors,mobile robots,radial basis function network | Computer vision,Radial basis function network,GRASP,Proximity sensor,Computer science,Sensor fusion,Artificial intelligence,Control system,Robot,Grippers,Mobile robot | Conference |
Citations | PageRank | References |
1 | 0.38 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hong Sun | 1 | 1 | 0.38 |
| Hai-chuan Zhu | 2 | 1 | 0.38 |
| Ting Wu | 3 | 3 | 0.89 |