Breast cancer is the most common type of cancer worldwide. A robotic system
performing autonomous breast palpation can make a significant impact on the
related health sector worldwide. However, robot programming for breast
palpating with different geometries is very complex and unsolved. Robot
learning from demonstrations (LfD) reduces the programming time and cost.
However, the available LfD are lacking the modelling of the manipulation
path/trajectory as an explicit function of the visual sensory information. This
paper presents a novel approach to manipulation path/trajectory planning called
deep Movement Primitives that successfully generates the movements of a
manipulator to reach a breast phantom and perform the palpation. We show the
effectiveness of our approach by a series of real-robot experiments of reaching
and palpating a breast phantom. The experimental results indicate our approach
outperforms the state-of-the-art method.

本文提出了基于深度运动原理的操作路径 / 轨迹规划的新方法，成功地生成了机械臂的运动，以到达乳房幻影并进行触诊，表明我们的方法优于现有方法。