RMCKF Scenario 2

Second scenario of the study: Regularized Maximum-Correntropy Criterion Kalman Filter for uncalibrated visual servoing in the presence of non-gaussian feature tracking noise. It presents a more complex visual servoing problem with non-gaussian noise contamination, where the robot starting configuration changes, requiring image features translation and rotation.本研究的第二场景：针对存在非高斯特征跟踪噪声（non-gaussian feature tracking noise）的未标定视觉伺服（uncalibrated visual servoing）问题的正则化最大互熵准则卡尔曼滤波器（Regularized Maximum-Correntropy Criterion Kalman Filter）。该场景涵盖更为复杂的受非高斯噪声污染的视觉伺服问题，此时机器人初始构型发生变化，且需完成图像特征的平移与旋转处理。