Name
Title | ||
|---|---|---|
Grid mapping in dynamic road environments: Classification of dynamic cell hypothesis via tracking |
Abstract | ||
|---|---|---|
We propose a method capable of acquiring an occupancy grid map-based representation of the local, static driving environment around an intelligent vehicle in the presence of dynamic objects. These corrupt the representation due to violating the underlying static-world assumptions of common grid mapping algorithms and are therefore detected and filtered from the map. For this purpose, a subsequent step is suggested that identifies, clusters and merges dynamic cell hypothesis in a novel way. Thereafter, an Interacting-Multiple-Model-Unscented-Kalman-Probabilistic-Data-Association (IMM-UK-PDA) tracker is used to classify of whether cell movements behave consistently with possible movement characteristics of real dynamic objects or are just generated by noise or newly observed static environment. In opposition to many other approaches, the method explicitly combines information of newly occupied and free areas, completes the shape of only partly visible dynamic objects and uses an advanced object tracking scheme to clean the grid from dynamic object corruptions. The method is evaluated with grids generated by an automotive radar and stereo camera in real traffic environments. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ICRA.2014.6907439 | Robotics and Automation |
Keywords | Field | DocType |
Kalman filters,automobiles,driver information systems,image classification,image fusion,image motion analysis,image representation,intelligent transportation systems,nonlinear filters,object detection,object tracking,IMM-UK-PDA tracker,advanced driver assistance systems,advanced object tracking scheme,automotive radar,dynamic cell hypothesis classification,dynamic object corruptions,dynamic road environments,intelligent vehicle,interacting-multiple-model-unscented-Kalman-probabilistic-data-association,local static driving environment,observed static environment,occupancy grid map-based representation algorithm,partly visible dynamic objects,real dynamic object movement characteristics,real traffic environments,static-world assumptions,stereo camera | Computer vision,Stereo camera,Automotive radar,Control engineering,Video tracking,Artificial intelligence,Engineering,Mapping algorithm,Grid,Occupancy grid mapping | Conference |
Volume | Issue | ISSN |
2014 | 1 | 1050-4729 |
Citations | PageRank | References |
5 | 0.44 | 17 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Matthias Schreier | 1 | 39 | 4.69 |
| Volker Willert | 2 | 154 | 25.48 |
| Jürgen Adamy | 3 | 192 | 39.49 |