期刊
IEEE-ASME TRANSACTIONS ON MECHATRONICS
卷 23, 期 3, 页码 1103-1113出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TMECH.2018.2816963
关键词
Collision-free navigation; convex quadratic programming (CQP); model predictive control (MPC); real time; vehicle shape
类别
资金
- National Natural Science Foundation of China [91420103, 61773289, 61733013]
- Shanghai Natural Science Foundation [17ZR1445800]
- Projects of Shanghai International Cooperation [18510711100]
- Fundamental Research Funds for the Central Universities
Collision-free navigation of autonomous vehicles by means of convex quadratic programming (CQP) based model predictive control (MPC) is considered in this paper. A new collision-free navigation function is designed for real-time collision avoidance of an autonomous vehicle in both static and dynamic environments. Furthermore, vehicle shape is taken into consideration during trajectory generation as a convex polygonal region defined by linear constraints rather than a single point. Then, the MPC optimization problem with the vehicle shape is solved as a CQP-based MPC scheme in the sense of path planning. Compared to the previous MPC, which can only be reduced to a nonlinear programming problem, the control sequences of CQP-based MPC can be obtained quickly with improved real-time system performance. Simulations in diverse scenarios, including a real vehicle dataset, show the validity of the proposed approach.
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