In this manuscript, an autonomous navigation algorithm for wheeled mobile robots (WMR) operating in dynamic environments (indoors or structured outdoors) is formulated. The planning scheme is of critical importance for autonomous navigational tasks in complex dynamic environments. In fast dynamic environments, path planning needs algorithms able to sense simultaneously a diversity of obstacles, and use such sensory information to improve real-time navigation control, while moving towards a desired goal destination. The framework tackles 4 issues. 1) Reformulation of the Social Force Model (SFM) adapted to WMR; 2) the cohesion of a general inertial scheme to represents motion in any coordinate system; 3) control of actuators rotational speed as a general model regardless kinematic restrictions; 4) assuming detection of features (obstacles/goals), adaptive numeric weights are formulated to affect navigational exponential components. Simulation and experimental outdoors results are presented to show the feasibility of the proposed framework.

中文翻译：

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WMR导航的指数字段公式

在此手稿中，制定了在动态环境（室内或室外结构化）中运行的轮式移动机器人（WMR）的自主导航算法。规划方案对于复杂动态环境中的自主导航任务至关重要。在快速动态的环境中，路径规划需要能够同时感测各种障碍物并使用此类感官信息来改善实时导航控制，同时又朝着理想的目标目的地前进的算法。该框架解决了4个问题。1）重新制定适合WMR的社会力量模型（SFM）；2）通用惯性方案的内聚性，以表示任何坐标系中的运动；3）不论运动学上的限制如何，作为一般模型控制执行器的转速；4）假设检测到特征（障碍物/目标），制定了自适应数字权重以影响导航指数分量。仿真和室外实验结果表明了该框架的可行性。