Differential drive robots that can be modeled as a kinematic unicycle are a standard mobile base platform for many service and logistics robots. Safe and smooth autonomous motion around obstacles is a crucial skill for unicycle robots to perform diverse tasks in complex environments. A classical control approach for unicycle control is feedback linearization using a headway point at a fixed headway distance in front of the unicycle. The unicycle headway control brings the headway point to a desired goal location by embedding a linear headway reference dynamics, which often results in an undesired offset for the actual unicycle position. In this paper, we introduce a new unicycle headway control approach with an adaptive headway distance that overcomes this limitation, i.e., when the headway point reaches the goal the unicycle position is also at the goal. By systematically analyzing the closed-loop unicycle motion under the adaptive headway controller, we design analytical feedback motion prediction methods that bound the closed-loop unicycle position trajectory and so can be effectively used for safety assessment and safe unicycle motion design around obstacles. We present an application of adaptive headway motion control and motion prediction for safe unicycle path following around obstacles in numerical simulations.

翻译：可建模为运动学独轮车的差速驱动机器人是许多服务与物流机器人的标准移动平台。在复杂环境中实现安全且平滑的自主避障运动，是独轮车机器人执行多样化任务的关键技能。一种经典控制方法是在独轮车前固定航向距离处设置航向点，通过反馈线性化实现控制。该航向控制方法通过嵌入线性航向参考动力学将航向点引导至目标位置，但这常导致实际独轮车位置产生非期望偏移。本文提出一种基于自适应航向距离的新型独轮车航向控制方法，克服了这一局限——当航向点到达目标时，独轮车位置亦同步抵达目标。通过系统分析自适应航向控制器作用下的闭环独轮车运动，我们设计了能界定闭环独轮车位置轨迹的解析反馈运动预测方法，可有效用于安全评估及障碍环境下的安全独轮车运动设计。数值仿真展示了基于自适应航向运动控制与运动预测的障碍环境下安全独轮车路径跟踪应用。