Performing swift and agile maneuvers is essential for the safe operation of autonomous mobile robots. Moreover, the presence of time-delay restricts the response time of the system and hinders the safety performance. Thus, this paper proposes a modular and scalable safety-control design that utilizes the Smith predictor and barrier certificates to safely and consistently avoid obstacles with different footprints. The proposed solution includes a two-layer predictor to compensate for the time-delay in the servo-system and angle control loops. The proposed predictor configuration dramatically improves the transient performance and reduces response time. Barrier certificates are used to determine the safe range of the robot's heading angle to avoid collisions. The proposed obstacle avoidance technique conveniently integrates with various trajectory tracking algorithms, which enhances design flexibility. The angle condition is adaptively calculated and corrects the robot's heading angle and angular velocity. Also, the proposed method accommodates multiple obstacles and decouples the control structure from the obstacles' shape, count, and distribution. The control structure has only eight tunable parameters facilitating control calibration and tuning in large systems of mobile robots. Extensive experimental results verify the effectiveness of the proposed safety-control.
翻译:执行快速和敏捷的操作是自动移动机器人安全操作的关键。 此外,时间延迟的存在限制了系统的反应时间,妨碍了安全性能。 因此,本文件建议采用模块和可扩缩的安全控制设计,使用史密斯预测器和障碍证书,安全和一贯地避免不同足迹造成的障碍。 拟议的解决方案包括一个双层预测器,以补偿瑟沃系统和角度控制环中的时间跨度。 拟议的预测器配置极大地改进了瞬时性能并缩短了反应时间。 使用障碍证书来确定机器人航向角度的安全范围以避免碰撞。 拟议的避免障碍技术与各种轨迹跟踪算法方便地结合,从而增强设计的灵活性。 角度条件是适应性计算并校正机器人航向角度和角速度。 另外, 拟议的方法还容纳了多种障碍,使控制结构与障碍的形状、计数和分布脱钩。 控制结构只有8个金枪鱼可参数, 便于在大型移动机器人系统中进行控制校准和调整。 大规模实验性控制的结果将核查拟议的安全性。