Orou Mousse Charifou, Benrabah Mohamed, Marmoiton François, Wilhelm Alexis, Chapuis Roland
Université Clermont Auvergne, Centre National de Recherche Scientifique, Clermont Auvergne INP, Institut Pascal UMR6602, F-63000 Clermont-Ferrand, France.
Sensors (Basel). 2023 Aug 17;23(16):7237. doi: 10.3390/s23167237.
The basic functions of an autonomous vehicle typically involve navigating from one point to another in the world by following a reference path and analyzing the traversability along this path to avoid potential obstacles. What happens when the vehicle is subject to uncertainties in its localization? All its capabilities, whether path following or obstacle avoidance, are affected by this uncertainty, and stopping the vehicle becomes the safest solution. In this work, we propose a framework that optimally combines path following and obstacle avoidance while keeping these two objectives independent, ensuring that the limitations of one do not affect the other. Absolute localization uncertainty only has an impact on path following, and in no way affects obstacle avoidance, which is performed in the robot's local reference frame. Therefore, it is possible to navigate with or without prior information, without being affected by position uncertainty during obstacle avoidance maneuvers. We conducted tests on an EZ10 shuttle in the PAVIN experimental platform to validate our approach. These experimental results show that our approach achieves satisfactory performance, making it a promising solution for collision-free navigation applications for mobile robots even when localization is not accurate.
自动驾驶车辆的基本功能通常包括通过沿着参考路径行驶并分析该路径上的可通行性来避开潜在障碍物，从而在世界中从一个点导航到另一个点。当车辆在定位方面存在不确定性时会发生什么情况？它的所有能力，无论是路径跟踪还是避障，都会受到这种不确定性的影响，而让车辆停下来就成为了最安全的解决方案。在这项工作中，我们提出了一个框架，该框架在保持路径跟踪和避障这两个目标相互独立的同时，对它们进行优化结合，确保一个目标的局限性不会影响另一个目标。绝对定位不确定性仅对路径跟踪有影响，而绝不会影响在机器人局部参考系中执行的避障操作。因此，无论有无先验信息都可以进行导航，在避障操作期间不会受到位置不确定性的影响。我们在PAVIN实验平台上的EZ10穿梭车上进行了测试，以验证我们的方法。这些实验结果表明，我们的方法取得了令人满意的性能，即使在定位不准确的情况下，它也是移动机器人无碰撞导航应用的一个有前景的解决方案。
