The ever-changing nature of human environments presents great challenges to robot manipulation. Objects that robots must manipulate vary in shape, weight, and configuration. Important properties of the robot, such as surface friction and motor torque constants, also vary over time. Before robot manipulators can work gracefully in homes and businesses, they must be adaptive to such variations. This survey summarizes types of variations that robots may encounter in human environments and categorizes, compares, and contrasts the ways in which learning has been applied to manipulation problems through the lens of adaptability. Promising avenues for future research are proposed at the end.

人类环境不断变化的性质给机器人操作带来了巨大的挑战。机器人必须操纵的物体的形状、重量和配置各不相同。机器人的重要属性，例如表面摩擦和电机扭矩常数，也会随时间变化。在机器人操纵器可以在家庭和企业中优雅地工作之前，它们必须适应这种变化。该调查总结了机器人在人类环境中可能遇到的变化类型，并通过适应性的视角对将学习应用于操作问题的方式进行分类、比较和对比。最后提出了未来研究的有希望的途径。