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:差动驱动机器人可以被建模为一个动力学独轮车,是许多服务和物流机器人的标准移动基础平台。在复杂环境中,安全而平稳地自主运动是独轮车机器人执行各种任务的关键技能。经典的独轮车控制方法是使用固定车头距离处的反馈线性化,将车头点引导到目标位置。独轮车车头控制通过嵌入线性的车头参考动态将车头点带到期望的目标位置,这通常会导致实际独轮车位置的不良偏差。在本文中,我们提出了一种新的独轮车车头控制方法,采用自适应车头距离,克服了这个局限性,即当车头点到达目标位置时,独轮车位置也在目标位置。通过系统分析闭环独轮车运动,在自适应车头控制器下设计了分析反馈运动预测方法,用于限制闭环独轮车的位置轨迹,因此可以有效地用于安全评估和安全绕过障碍物的独轮车运动设计。我们提出了自适应车头运动控制和运动预测的应用,用于数值仿真中安全的独轮车路径跟踪绕过障碍物。