Socially Assistive Robots Serving Children with Special Needs (Autism, Cancer, Deafness/Hearing Loss)

Meghdari A F
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Abstract

One of the main challenges in social and cognitive research is relevant to our understanding of how to perceive and interact with others in the world around us. With the dramatic growth of emerging technologies in our societies, such as social robots, computer graphic generated avatars, and virtual reality devices, the complexity of this challenge is growing. As a result, interdisciplinary educators and researchers strive to determine the extent neurocognitive mechanisms, which support human interaction with artificial agents and tools, have evolved. Hence, a growing number of researchers working within the field of social robotics and engineering are engaged in collaboration with other scientists to utilize their expertise in social cognition, neuroscience, linguistics, and psychology with mutual interests that benefits naturally developing children as well as children with some form of disability and/or illness (i.e. Kids with: autism, cancer, deafness/hearing loss, down syndrome, diabetes, etc.). With the advancement of robotics technology, robots applications have been extended to more general-purpose practices in society such as: the use of robots in clinical and rehabilitation, nursing and elderly care, search and rescue operations, etc. However, for robotics technology to be successful in such environments it is necessary to gain new levels of strength, robustness, physical skills, and improved cognitive ability and intelligence. One faces many challenges on the path to design and construction of social-cognitive robots, the biggest is to build robots that comply with the needs and expectations of the human mind. How we communicate with machines with a higher quality physical and life-like appearance would differ with the way we interact with a computer, cell phone, or other smart devices. Therefore, as a follow up to the classical view of robotic systems, “socially interactive robots” with the capability of engaging social scenarios and interacting with humans have recently become a trendy and upto- date topic. In recent years, the impacts of employing social robots as teaching assistants on enhancing learners’ achievements notably in children with special needs were investigated by various researchers. In addition, these robots can be effectively employed in diverse healthcare applications. For instance, the positive effects of utilizing social robots in decreasing the distress level of children with cancer through establishing affective connection with patients was highlighted. Furthermore, they have been successfully utilized to improve the imitation skills of children with Autism Spectrum Disorder (ASD), which is known to be one of the core symptoms. In addition, social robots have been designed to play an assistive role in expanding the communication level of deaf and ordinary children in teaching them Sign Language. For instance, it has been noted that for social robots to achieve success in their mission, adaptive user interfaces lead to greater user acceptance and increased teaching efficiency compared to non-adaptive ones. Hence, one need to design and build a robotic architecture capable of simultaneously adjusting the robot’s teaching parameters according to both the user’s past and present performance, adapt the content of training, and then implement it on the social robot to teach sign language based on these parameters in a manner similar to a human teacher. On the other hand, empowering a robot to direct its attention to the most appropriate target at all times during multi-party interactions is another interesting and useful task to establish natural communication between the robot and users. Implementing a social gaze control system suitable for multiperson interactions with the social robot is another challenging topic, which may be done such that the system takes some important verbal and non-verbal social cues into account and at each moment enable the robot to decide socially at which human it should direct its gaze.
为有特殊需要的儿童(自闭症、癌症、耳聋/听力损失)提供社交辅助机器人
社会和认知研究的主要挑战之一与我们对如何感知周围世界并与之互动的理解有关。随着社会中新兴技术的迅猛发展,例如社交机器人、计算机图形生成的化身和虚拟现实设备,这一挑战的复杂性正在增长。因此,跨学科教育工作者和研究人员努力确定支持人类与人工代理和工具互动的神经认知机制的发展程度。因此,越来越多的研究人员在社会机器人和工程领域与其他科学家合作,利用他们在社会认知、神经科学、语言学和心理学方面的专业知识,共同利益,使自然发育的儿童以及患有某种形式残疾和/或疾病的儿童(即患有自闭症、癌症、耳聋/听力损失、唐氏综合症、糖尿病等的儿童)受益。随着机器人技术的进步,机器人的应用已经扩展到社会上更多的通用实践,例如:机器人在临床和康复、护理和老年人护理、搜索和救援行动等方面的使用。然而,机器人技术要想在这样的环境中取得成功,就必须提高力量、健壮性、身体技能以及提高认知能力和智力。在设计和制造社会认知机器人的道路上,人们面临着许多挑战,其中最大的挑战是制造符合人类思维需求和期望的机器人。我们与具有更高质量物理和逼真外观的机器交流的方式,将与我们与计算机、手机或其他智能设备互动的方式不同。因此,作为机器人系统经典观点的后续,具有参与社会场景和与人类互动能力的“社会互动机器人”最近成为一个时髦和最新的话题。近年来,各种研究人员调查了使用社交机器人作为教学助理对提高学习者成绩的影响,特别是在有特殊需要的儿童中。此外,这些机器人可以有效地应用于各种医疗保健应用。例如,利用社交机器人通过与患者建立情感联系来降低癌症儿童的痛苦程度的积极作用得到了强调。此外,它们已被成功地用于改善自闭症谱系障碍(ASD)儿童的模仿技能,这是已知的核心症状之一。此外,社交机器人被设计为在聋哑儿童和普通儿童的手语教学中发挥辅助作用,以扩大他们的沟通水平。例如,人们已经注意到,社交机器人要成功完成任务,自适应用户界面比非自适应用户界面更容易被用户接受,并提高教学效率。因此,需要设计和构建一个机器人架构,能够根据用户过去和现在的表现同时调整机器人的教学参数,适应训练内容,然后在社交机器人上实现它,以类似于人类教师的方式基于这些参数教授手语。另一方面,授权机器人在多方交互过程中始终将其注意力引导到最合适的目标上是另一个有趣且有用的任务,可以在机器人和用户之间建立自然通信。实现适合与社交机器人进行多人交互的社交凝视控制系统是另一个具有挑战性的主题,可以这样做,系统考虑一些重要的语言和非语言社交线索,并在每个时刻使机器人能够社会性地决定应该将目光投向哪一个人。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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