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The two primary segments for robotics are industrial and non-industrial industry verticals.
Historically closely associated with a manufacturing environment, robots are moving beyond the realm of traditional use cases, such as assembling of parts in the automobile industry, and becoming widely used in military, healthcare, retail, construction, and other industries.
Robotics is increasingly becoming more mainstream and seen in many aspects of daily life in non-industrial markets such as autonomous vehicles, consumer robots, and unmanned aerial vehicles.
While industrial robots play a major role in factory automation, non-industrial robots find use in agriculture, construction, logistics, telepresence, and customer service. These are application markets where significant growth is expected.
Mind Commerce expects robots to become more ubiquitous, delivering efficiencies to services that were previously inconceivable. For example, cloud robotics will tremendously expand user access through robotics as a service.
Leveraging Machine to Machine communications and the Internet of Things (IoT) will enable robotics to seamlessly communicate with a wide variety of devices and applications, which will enable greater utility and learning through exchange of information with different robotic systems.
Robotics in contemporary manufacturing have largely been purpose-specific and contained within cages for security and safety. Next generation robots are often times mobile (cage free) and many are collaborative with humans (e.g. cobots). Legacy robots function to replace the workforce to perform repetitive work such as assembly processes. While these types of robots continue to have a purpose, cobots are used in situations that require greater flexibility and finesse enabled through collaboration with a human operator.
Next generation smart factors and other industrial verticals are also looking towards operating robots that are both automated and learning machines. Autonomous robots use various aspects of AI to gain information from the environment and perform tasks for longer period of times without human intervention. These smart bots automatically learn from the environment and adjust methods of task completion with changing scenarios.