Name
Abstract | ||
|---|---|---|
This paper presents an approach to sensor planning for simultaneous pose estimation and model identification of a moving object using a stereo camera sensor mounted on a mobile base. For a given database of object models, we consider the problem of identifying an object known to belong to the database and where to move next should the object not be easily identifiable from the initial viewpoint. No constraints on the motion of the object nor the robot itself are assumed, which is an improvement on previous methods. Sensor planning is based on the selection of the control action that optimizes a cost metric based on information gain. Experimental results from the implementation of the method on a two-wheeled nonholonomic robot are presented to illustrate and validate the method. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ROBOT.2010.5509205 | Robotics and Automation |
Keywords | Field | DocType |
cameras,mobile robots,path planning,pose estimation,robot dynamics,robot vision,stereo image processing,cost metric,dynamic sensor planning,information gain,mobile platform,model identification,pose estimation,stereo camera sensor,two-wheeled nonholonomic robot | Motion planning,Stereo camera,Computer vision,Data modeling,Control engineering,Pose,Artificial intelligence,Engineering,Robot,System identification,Mobile robot,Cognitive neuroscience of visual object recognition | Conference |
Volume | Issue | ISSN |
2010 | 1 | 1050-4729 E-ISBN : 978-1-4244-5040-4 |
ISBN | Citations | PageRank |
978-1-4244-5040-4 | 4 | 0.60 |
References | Authors | |
9 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jeremy Ma | 1 | 181 | 9.93 |
| Burdick, J.W. | 2 | 2988 | 516.87 |