运动规划
规划师
计算机科学
机器人学
路径(计算)
人工智能
计算
机器人
质量(理念)
曲率
计算机视觉
模拟
控制工程
实时计算
工程类
数学
算法
认识论
哲学
程序设计语言
几何学
作者
Domokos Kiss,Dávid Papp
标识
DOI:10.1109/sami.2017.7880346
摘要
Development of driverless road vehicles is one of the most active research areas of robotics today. Path planning among obstacles is one of the challenging problems to be solved in order to achieve autonomous navigation. In this paper we present a geometric path planning approach for car-like robots, intended for generating good quality paths even in cluttered environments containing narrow areas. The presented planner is designed to cope with situations which need nontrivial maneuvering between obstacles. The resulting paths are similar to those a human driver would find and have continuous curvature profile, which makes them appropriate for application on real cars. A comparative analysis of our method with possible alternatives in the literature is presented to illustrate its effectiveness regarding path quality and computation time.
科研通智能强力驱动
Strongly Powered by AbleSci AI