Optimization-Based Hierarchical Motion Planning for Autonomous Racing
| Autor: | Vázquez, José L., Brühlmeier, Marius, Liniger, Alexander, Rupenyan, Alisa, Lygeros, John |
|---|---|
| Rok vydání: | 2020 |
| Předmět: | |
| Druh dokumentu: | Working Paper |
| Popis: | In this paper we propose a hierarchical controller for autonomous racing where the same vehicle model is used in a two level optimization framework for motion planning. The high-level controller computes a trajectory that minimizes the lap time, and the low-level nonlinear model predictive path following controller tracks the computed trajectory online. Following a computed optimal trajectory avoids online planning and enables fast computational times. The efficiency is further enhanced by the coupling of the two levels through a terminal constraint, computed in the high-level controller. Including this constraint in the real-time optimization level ensures that the prediction horizon can be shortened, while safety is guaranteed. This proves crucial for the experimental validation of the approach on a full size driverless race car. The vehicle in question won two international student racing competitions using the proposed framework; moreover, our hierarchical controller achieved an improvement of 20% in the lap time compared to the state of the art result achieved using a very similar car and track. Comment: Submitted to IROS |
| Databáze: | arXiv |
| Externí odkaz: |
|