期刊
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
卷 88, 期 1, 页码 129-146出版社
SPRINGER
DOI: 10.1007/s10846-017-0531-8
关键词
Continuous curvature path planning; Iterative algorithm; Minimax sharpness constraint; Nonholonomic car-like vehicle; Curvature and sharpness diagram
资金
- National Research Foundation (NRF) - Korean Ministry of Science, ICT and Planning (MSIP) [NRF-2013M1A3A3A02042335]
- Korea Evaluation Institute of Industrial Technology (KEIT) - Korean Ministry of Trade, Industry and Energy (MOTIE) [2015-10060160]
- French National Research Agency (ANR) through LabEx IMobS3 [ANR-7107-LABX-716701]
This paper addresses a continuous curvature path generation problem for car-like vehicle navigation. The continuous curvature path is generated by multiple clothoids composition and parametric adjustment. According to the geometric conditions of the given initial and final configurations, the path generation problem is classified into two cases and then, each problem is solved by by appropriate proposed algorithm. The solution is obtained by iterative procedure subject to geometric constraint as well as solution constraints. For computational efficiency and fast convergence in the proposed algorithms, a minimax sharpness constraint is proposed as the solution constraint by minimizing the maximum sharpness of the feasible solutions. After the generation of the proposed path, the resultant curvature/sharpness diagram provides a useful information about its orientation and curvature continuity along the travel length. The proposed path planning strategy, permits us to obtain online, smooth and safe path between two defined configurations while ensuring high passengers comfort (continuous curvature and transition between the different composed clothoids). The algorithmic proposals have been applied to generate continuous curvature for two cases. The first correspond to local path planning for ensuring obstacle avoidance or lane change. The second application corresponds to global path smoothing. The resultant global path path is tested on the Lyapunov-based control scheme and showed improved performance on its steering work (reduction of 41.0% than the driving based on the raw data), which permits us therefore to validate the effectiveness of the obtained global path for car-like vehicles path following.
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