弹道
地形
卡车
计算机科学
运动学
运动规划
平面图(考古学)
采样(信号处理)
数学优化
轨迹优化
运筹学
数据挖掘
工程类
机器人
数学
人工智能
地理
物理
地图学
考古
滤波器(信号处理)
经典力学
天文
航空航天工程
计算机视觉
作者
Fangyin Tian,Rui Zhou,Zhiheng Li,Li Li,Yu Bao Gao,Dongpu Cao,Long Fei Chen
标识
DOI:10.1109/tiv.2021.3065867
摘要
There are many constraints to be considered to plan a safe and feasible trajectory for autonomous mining trucks due to the rough terrain in open-pit mines. It is difficult to handle these constraints uniformly within a trajectory planning framework. To overcome this limitation, a novel trajectory planning framework is proposed in this paper. Different from many existing studies which characterized the spatial positions of vehicles at the sampling time points as decision variables, we characterize the time points at the sampling spatial positions as decision variables to conveniently address the terrain constraints. Based on such a formulation, we further consider the kinematic constraints, engine power constraints and time window constraints. Various objectives (e.g., transport efficiency, fuel economy) can be considered in this trajectory planning framework, and the formulated trajectory planning problems can be efficiently solved. Finally, several case studies are conducted to validate the effectiveness of the proposed trajectory planning framework.
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