Social Robot Market Analysis

End-User (Healthcare, Education, Entertainment, Retail)

The healthcare segment in the social robots market is estimated to gain a robust revenue share of 40% in the coming years owing to the growing burden of autism among children. Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that affects social life and is one of the most debilitating developmental disorders. Moreover, ASD can lead to severe difficulties with behavior, and social interaction, and can impede the language and communication development of children.

For kids with autism spectrum disorders (ASDs), robots-assisted treatment (RAT) is a promising field in translational neuroscience as they have been found to have a favorable effect on their ability to imitate, make eye contact, and exhibit repetitive and stereotyped behavior. Social robotss are being employed more and more as mediators between a child and a therapist since they are less frightening than humans and have a solid, three-dimensional presence. For instance, Orbit, an interactive robots, hopes to educate kids with autism spectrum disorders (ASD) about emotions and teaches kids how to build social appropriateness through visual communication, physical engagement, and storytelling.

According to the World Health Organization (WHO), globally, an estimated 1 in 100 children suffer from autism.

In addition, social robotss can take on a variety of roles to assist or instruct pupils while they study as they are capable of filling a variety of positions, such as novice, tutor, and teaching assistant. In education, social robotss are being utilized more and more, and over time, they have become more and more common, and have demonstrated efficacy in improving cognitive and affective outcomes, and on limited tasks, they have produced results comparable to those of human tutoring.

Technology (Machine Learning, Computer Vision, Context Awareness, Natural Language Processing)

The machine learning segment in the social robots market is set to garner a notable share shortly. Robotss with machine learning algorithms installed can learn about their environment and how to interact with it by analyzing large volumes of data and adjust to changing environments since they can recognize patterns, and anticipate outcomes. Moreover, machine learning-equipped social robotss can identify speech patterns, comprehend context, identify emotions from voice tonality, and can recognize and interact with items in their environment with previously unheard-of precision and dexterity.

Our in-depth analysis of the global social robots market includes the following segments: