| Full text | |
| Author(s): |
Battagello, Vinicius Antonio
;
Soma, Nei Yoshihiro
;
Magalhaes Afonso, Rubens Junqueira
;
IEEE
Total Authors: 4
|
| Document type: | Journal article |
| Source: | 2021 AMERICAN CONTROL CONFERENCE (ACC); v. N/A, p. 6-pg., 2021-01-01. |
| Abstract | |
In this paper we propose a technique that assigns obstacles to clusters used for collision avoidance via Mixed-Integer Programming. This strategy enables a reduction in the number of binary variables used for collision avoidance, thus entailing a decrease in computational cost, which has been a hindrance to the application of Model Predictive Control approaches with Mixed-Integer Programming formulations in real-time. Moreover, the assignment of obstacles to clusters and the sizes of the clusters are decided within the same optimization problem that performs the trajectory planning, thus yielding optimal cluster choices. Simulation results are presented to illustrate an application of the proposal. (AU) | |
| FAPESP's process: | 16/01860-1 - Cutting, packing, lot-sizing, scheduling, routing and location problems and their integration in industrial and logistics settings |
| Grantee: | Reinaldo Morabito Neto |
| Support Opportunities: | Research Projects - Thematic Grants |