Name
Abstract | ||
|---|---|---|
We analyze the relationship between classification performance (i.e., the mutual information and the probability of misclassification) and sensor abilities. The analysis suggests an effective region of sensor space that can improve the classification performance when multiple measurements are to be taken sequentially, and possible sensor allocation strategies are discussed. Based on the analysis, we apply the sensing strategies to a UAV path planning problem where the sensor performance depends on the relative position (i.e., range and azimuth) of the UAV with respect to the object of interest. Specifically, we use two sliding mode controllers, each of which accounts for a particular sensing strategy, with a hybrid-system switching scheme. We validate our approach with numerical simulation results. |
Year | Venue | Keywords |
|---|---|---|
2013 | Control Conference | autonomous aerial vehicles,numerical analysis,path planning,pattern classification,robot kinematics,sensors,variable structure systems,uav kinematics,uav path planning problem,azimuth,classification performance improvement,hybrid-system switching scheme,misclassification probability,mutual information,numerical simulation,object-of-interest,range,relative position,sensor allocation strategies,sensor performance,sensor space,sliding mode controllers,kinematics |
Field | DocType | Citations |
Motion planning,Kinematics,Computer simulation,Robot kinematics,Azimuth,Control engineering,Mutual information,Engineering,Numerical analysis | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Weijia Zhang | 1 | 0 | 0.34 |
| Baro Hyun | 2 | 18 | 3.84 |
| Kabamba, P. | 3 | 0 | 0.34 |
| Anouck R. Girard | 4 | 15 | 2.65 |