论文标题
基于切换运动轨迹的高斯过程的视觉追击控制
Visual Pursuit Control based on Gaussian Processes with Switched Motion Trajectories
论文作者
论文摘要
本文考虑了追求移动目标的方案，该方案可能通过使用视觉传感器进行运动估算中的动态环境中的外部因素来切换行为。首先，我们提供了一个改进的视觉运动观察者，其中包括一类扩展目标运动曲线的切换高斯工艺模型。然后，我们通过在线方法提出了一项追求控制法，以通过GP模型不确定性估算目标的转换行为。接下来，我们证明了目标行为转换的控制和估计误差的最终界限，概率很高。最后，数字双模拟证明了拟议的切换估计和控制法的有效性，以证明对现实世界情景的适用性。
This paper considers a scenario of pursuing a moving target that may switch behaviors due to external factors in a dynamic environment by motion estimation using visual sensors. First, we present an improved Visual Motion Observer with switched Gaussian Process models for an extended class of target motion profiles. We then propose a pursuit control law with an online method to estimate the switching behavior of the target by the GP model uncertainty. Next, we prove ultimate boundedness of the control and estimation errors for the switch in target behavior with high probability. Finally, a Digital Twin simulation demonstrates the effectiveness of the proposed switching estimation and control law to prove applicability to real world scenarios.
