Energy Management of Planetary Rovers Using a Fast Feature-Based Path Planning and Hardware-in-the-Loop Experiments
Energy Management of Planetary Rovers Using a Fast Feature-Based Path Planning and Hardware-in-the-Loop Experiments
复制标题
使用基于特征的快速路径规划和硬件在环实验进行行星漫游者的能源管理
DOI：
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发表时间：
2013
影响因子：
6.8
通讯作者：
A. Khajepour
中科院分区：
文献类型：
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作者：
Saber Fallah;Bonnie Yue;Orang Vahid;A. Khajepour
本文提出了一种新的基于特征的路径优化方法，该方法定义了综合考虑地形、运动学和动态约束的性能指标，使漫游车的能量消耗最小。该方法通过对路径进行离散化并提取统计数据来快速计算性能指标，从而估计漫游车的能耗。使用分组数据的概念和数据离散化技术来分析从搜索环境中获得的与能源相关的数据。该方法通过统计计算漫游车在指定路径下的能量消耗，而不是求解漫游车的动力学方程，从而改进了运行时计算。当它以足够的精度估计漫游车的能量消耗时，该技术在计算上比其他能量优化方法更有效。将遗传算法(GA)的求解器集成到该方法中，验证了算法的有效性。此外，还开发了半实物仿真(HIL)，通过在实时仿真中加入漫游车硬件组件来验证漫游车通过最优路径时的功率流。
This paper presents a novel feature-based technique for path optimization problems, in which the performance index is defined to minimize the energy consumption of a rover with consideration of terrain, kinematic, and dynamic constraints. The proposed method estimates rover energy consumption by discretizing a path and by extracting statistical data for fast calculation of the performance index. The concepts of grouped data and data discretization techniques are used to analyze the energy-related data obtained from the search environment. The method improves runtime computation by statistically calculating the energy consumption of a rover for a defined path, rather than solving the dynamic equations of the rover. This technique is computationally more efficient than other energy optimization approaches when it estimates rover energy consumption with sufficient accuracy. The Genetic Algorithm (GA) solver is integrated to the approach to illustrate the efficiency of the algorithm. Additionally, a hardware-in-the-loop (HIL) simulation is developed for the validation of the rover's power flow as it traverses through the optimal path by incorporating rover hardware components within real-time simulation.