Name
Abstract | ||
|---|---|---|
Obstacle avoidance problems are a class of non-convex optimal control problems for which derivative-based optimization algorithms often fail to locate global minima. The goal of this paper is to provide a tutorial on how to apply Branch & Lift algorithms, a novel class of global optimal control methods, for solving such obstacle avoidance problems to global optimality. The focus of the technical developments is on how Branch & Lift methods can exploit the particular structure of Dubin models, which can be used to model a variety of practical obstacle avoidance problems. The global convergence properties of Branch & Lift in the context of obstacle avoidance is discussed from a theoretical as well as a practical perspective by applying it to a tutorial example. |
Year | Venue | Field |
|---|---|---|
2017 | 2017 IEEE 56TH ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC) | Convergence (routing),Obstacle avoidance,Lift (force),Mathematical optimization,Optimal control,Computer science,Visualization,Control theory,Algorithm,Exploit,Maxima and minima,Trajectory |
DocType | ISSN | Citations |
Conference | 0743-1546 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xuhui Feng | 1 | 0 | 1.01 |
| Mario Eduardo Villanueva | 2 | 33 | 6.10 |
| Benoît Chachuat | 3 | 125 | 10.89 |
| Boris Houska | 4 | 214 | 26.14 |