Name
Abstract | ||
|---|---|---|
Varying terrain conditions influencing the ground friction challenge model-based control methods for precise autonomous driving of agricultural vehicles on off-road terrains. We apply moving horizon estimation (MHE) to cope with these uncertainties in a predictive control framework for autonomous driving of a sensor-equipped tractor using a (nonlinear) rigidbody dynamic model featuring a simple tire slip model. Using the ACADO Code Generation tool feedback times in the range of few miliseconds are achieved. Estimation results on real-world experimental data are presented. |
Year | Venue | Keywords |
|---|---|---|
2013 | Control Conference | agricultural machinery,control engineering computing,predictive control,remotely operated vehicles,road vehicles,vehicle dynamics,acado code generation tool,mhe,agricultural vehicles,autonomous driving,autonomous operation,ground friction,model-based control methods,moving horizon observation,off-road terrains,predictive control framework,rigidbody dynamic model,sensor-equipped tractor,terrain conditions,real time systems,estimation,sensors,tires |
Field | DocType | Citations |
Remotely operated underwater vehicle,Nonlinear system,Model predictive control,Terrain,Horizon,Control engineering,Code generation,Vehicle dynamics,Engineering,Tractor | Conference | 0 |
PageRank | References | Authors |
0.34 | 3 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Frasch, J.V. | 1 | 0 | 0.34 |
| Kraus, T. | 2 | 0 | 0.68 |
| Wouter Saeys | 3 | 78 | 11.04 |
| Moritz Diehl | 4 | 1343 | 134.37 |