The Boston Consulting Group is conservatively projecting that the market will reach USD 87 billion by 2025.
Source: The Robot Report
Electrical engineering company Siemens predicts the global market for autonomous robots to grow to USD 3.6 billion in 2019, and USD 13.9 billion in 2023.
The global autonomous robot market was valued at around USD 4.6 billion in 2016 and it is expected to reach more than USD 11.9 billion million by 2024. It is expected to grow at a CAGR of over 14% between 2017 and 2024.
Source: Global Newswire
When are autonomous robots practical?
Autonomous robots are particularly useful when one of the two criteria are met:
1. The environment is either dangerous or expensive for humans to operate in. For example, spaceflight and mine sweeping are both dangerous fields of human activity. Spaceflight is also extremely expensive due to the cost of supporting human life in space.
2. The task requires simple, routine action in high volume with a modest level of dynamic adjustment. For example, store-to-door goods delivery and highway trucking are both routine activities yet require the ability to react to unexpected situations within a range of possibilities. Likewise, in a production environment, a robot performs a largely repetitive action but must respond to unpredicted variables such as the precise orientation of a component it is assembling, or modification of the task in order to customize orders.
What are the core functionalities of an autonomous robot?
The concept of an autonomous robot is broad and can include a wide range of devices with very different capabilities. However, any autonomous robot should have some ability to perform these basic functions:
1. Gather and process information about the environment.
2. Work for an extended period without human intervention under unpredictable stimuli.
3. Move through its operating environment without human assistance (but with pre-determined constraints).
4. Avoid situations that it has been programmed to identify as undesirable, such as harm to people, property, or itself.
More advanced robots may be capable of optimizing their efficiency or adding new capabilities as they 'learn' through by processing data. The capabilities of robots can also be improved through system upgrades enabled by collective data processing. For example, a fleet of vehicles could receive regular updates that incrementally improve fuel efficiency based on the processing of their collective operational data under diverse driving conditions.