Potential Gap: A Gap-Informed Reactive Policy for Safe Hierarchical Navigation
Potential Gap: A Gap-Informed Reactive Policy for Safe Hierarchical Navigation
复制标题
潜在差距：用于安全分层导航的差距通知反应策略
DOI：
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发表时间：
2021
影响因子：
5.2
通讯作者：
P. Vela
中科院分区：
文献类型：
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作者：
Ruoyang Xu;Shiyu Feng;P. Vela
这封信认为，基于间隙的本地导航方法与人工势场（APF）的方法，以获得一个本地规划模块，称为潜在的差距，分层导航系统的集成。中央建设的本地规划是使用感官派生的本地自由空间模型，检测差距，并使用它们的合成的APF。从APF导出的轨迹是可证明的碰撞自由的理想化的机器人模型。当应用于更现实的模型时，可证明属性会丢失。一组算法修改纠正这些错误，并提高鲁棒性非理想模型，特别是非完整机器人模型。将潜在间隙局部规划器集成到分层导航系统中提供了通过未知环境的无碰撞导航所需的局部目标和轨迹。在基准世界的Monte Carlo实验证实了断言的安全性和鲁棒性。
This letter considers the integration of gap-based local navigation methods with artificial potential field (APF) methods to derive a local planning module, called potential gap, for hierarchical navigation systems. Central to the construction of the local planner is the use of sensory-derived local free-space models that detect gaps and use them for the synthesis of the APF. Trajectories derived from the APF are provably collision-free for idealized robot models. The provable property is lost when applied to more realistic models. A set of algorithm modifications correct for these errors and enhance robustness to non-ideal models, in particular a nonholonomic robot model. Integration of the potential gap local planner into a hierarchical navigation system provides the local goals and trajectories needed for collision-free navigation through unknown environments. Monte Carlo experiments in benchmark worlds confirm the asserted safety and robustness properties.