Name
Abstract | ||
|---|---|---|
This article describes a method for real-time integrated motion planning and control aimed at autonomous vehicles. Our method leverages feedback control, positive invariant sets, and equilibrium trajectories of the closed-loop system to produce and track trajectories that are collision-free with guarantees according to the vehicle model. Our method jointly steers the vehicle to a target region and controls the velocity while satisfying constraints associated with future motion of surrounding obstacles. We develop a receding-horizon implementation of the control policy and verify the method in both a simulated road scenario and an experimental validation using a scaled mobile robot with car-like dynamics using only onboard sensing. The results show that our method generates dynamically feasible and safe (i.e., collision-free) trajectories in real time, and indicate that the proposed planner is robust to sensing and mapping errors. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/TIV.2019.2955371 | IEEE Transactions on Intelligent Vehicles |
Keywords | DocType | Volume |
Trajectory,Planning,Robot sensing systems,Real-time systems,Roads,Vehicle dynamics | Journal | 5 |
Issue | ISSN | Citations |
1 | 2379-8858 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Karl Berntorp | 1 | 26 | 16.30 |
| Richard Bai | 2 | 0 | 0.34 |
| Karl F. Erliksson | 3 | 0 | 0.34 |
| Claus Danielson | 4 | 18 | 7.15 |
| Avishai Weiss | 5 | 0 | 0.68 |
| Stefano Di Cairano | 6 | 309 | 44.69 |