论文标题
个性化行为模型：一项针对自闭症治疗应用的调查
Personalized Behaviour Models: A Survey Focusing on Autism Therapy Applications
论文作者
论文摘要
自闭症谱系障碍的儿童发现机器人比人类更容易沟通。因此，已经在自闭症疗法中引入了机器人。但是，由于环境复杂性，通常必须手动控制使用的机器人。这是此类系统的重要缺点，需要使它们更自治。特别是，机器人应解释孩子的状态并根据治疗中儿童的行为不断适应其行为。该调查详细阐述了不同形式的个性化机器人行为模型。讨论了人类机器人相互作用领域的各种方法以及儿童机器人相互作用。目的是将它们的缺陷，实际情况的可行性以及对自闭症特异性机器人辅助治疗的潜在可用性进行比较。基于机器人在治疗游戏中学习适当互动策略的算法的一般挑战是提高机器人的自主权，从而为机器人的决策提供了基础。
Children with Autism Spectrum Disorder find robots easier to communicate with than humans. Thus, robots have been introduced in autism therapies. However, due to the environmental complexity, the used robots often have to be controlled manually. This is a significant drawback of such systems and it is required to make them more autonomous. In particular, the robot should interpret the child's state and continuously adapt its actions according to the behaviour of the child under therapy. This survey elaborates on different forms of personalized robot behaviour models. Various approaches from the field of Human-Robot Interaction, as well as Child-Robot Interaction, are discussed. The aim is to compare them in terms of their deficits, feasibility in real scenarios, and potential usability for autism-specific Robot-Assisted Therapy. The general challenge for algorithms based on which the robot learns proper interaction strategies during therapeutic games is to increase the robot's autonomy, thereby providing a basis for a robot's decision-making.
