Recently, Model Predictive Path Integral (MPPI) control algorithm has been extensively applied to autonomous navigation tasks, where the cost map is mostly assumed to be known and the 2D navigation tasks are only performed. In this paper, we propose a generic MPPI control framework that can be used for 2D or 3D autonomous navigation tasks in either fully or partially observable environments, which are the most prevalent in robotics applications. This framework exploits directly the 3D-voxel grid acquired from an on-board sensing system for performing collision-free navigation. We test the framework, in realistic RotorS-based simulation, on goal-oriented quadrotor navigation tasks in a cluttered environment, for both fully and partially observable scenarios. Preliminary results demonstrate that the proposed framework works perfectly, under partial observability, in 2D and 3D cluttered environments.

翻译：最近,模型预测路径综合控制算法(MPPI)被广泛应用于自主导航任务,其中成本图被认为大多为人所知,而2D导航任务只执行。在本文件中,我们提出了一个通用的移动电话综合控制框架,可以在完全或部分可观测的环境中用于2D或3D自主导航任务,这是机器人应用中最普遍的。这个框架直接利用从机载遥感系统中获取的用于进行无碰撞导航的3D-voxel电网。我们在现实的 RotorS模拟中测试该框架,以完全和部分可观测情景为对象,在封闭环境中进行面向目标的孔径仪导航任务。初步结果显示,拟议的框架在部分可观测的情况下,在2D和3D封闭环境中运作完美。