Collaborative Robot Market and its key opportunities and challenges

The collaborative robot market is estimated to be valued at USD 12,303 million by 2025, at a CAGR of 50.31% between 2017 and 2025 as per a report by MarketsandMarkets.

Why demand for high-payload-capacity co-bots to generate more opportunities?

ISO, ANSI, the Canadian Standards Association (CSA), and the Occupational Safety and Health Administration (OSHA) outline specific or minimum working conditions for collaborative robots that need to be fulfilled to avoid injuries and accidents. These standards include norms (e.g., ISO 10218 part 1 and 2 and ISO/TS 15066) that manufacturers follow for developing collaborative robots. These norms have been developed considering human safety as important; industrial robots require added safety fences to operate on the work floor. Such developments for standardizing the working environment of co-bots further add to the credibility of this technology. Technological advancements in co-bots, enhancing the ability to carry heavy payloads, would be the biggest innovation in the field of automation with maximum dexterity.

This concept implies that there are more potential consumers/users for heavy-payload collaborative robots, and it also signifies that there would be an increase in the number of industries to look after human–robot collaboration. In Japan, a co-bot is being developed by FANUC Corporation (Japan), which can handle a payload of 35kg, much more than any of its competitors’, and is ISO certified. Comau S.p.A (Italy) is another player exploring the field of collaborative robots with high payload capacity. Rising demand for high-payload-capacity co-bots in industries such as automotive, furniture and equipment, and metals and machining is the key driving factor for the growth of co-bots with >10kg payload capacity, as this category of co-bots holds strong potential to give tough competition to comparable payload capacity industrial robots owing to the discussed advantages of co-bots over industrial robots.

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Is developing AI to help robots make better decisions and make them safe for humans posing major challenge?

Over the years, robots have become smarter and more autonomous; however, they still lack apt cognitive ability. The colossal hurdle to the cognitive ability is attributable to highly unpredictable nature of human behavior and thought process, thereby creating a challenge to create a truly collaborative environment. As the cognitive behavior of humans is culturally specific, evolving continuously, and eternally debated, developing a perfect AI system is a major challenge faced by the providers of AI technology for the robotics market. With rising complexities in tasks performed at manufacturing facilities and the inherent quality of collaborative robots requiring easy programming or training on hand-guided movements via teach pendant, the integration of AI into co-bots might create more challenges for robot programmers. Also, there have been incidences wherein program developers working on AI platform had to abandon their projects as the robots or programs they developed behaved inexplicably. For instance, in July 2017, Facebook abandoned an experiment after 2 AI-based programs appeared to be chatting with each other in an unnatural language, which only they could understand. Such incidences have put forth a challenge for the manufacturers of AI-integrated robots to make them safe for humans.

Lack of capabilities related to faster cycle time and repeatability

Collaborative robots offer several advantages over traditional industrials robots; however, they do not offer high-speed operations. The norms defined by the International Organization for Standardization (ISO) and the American National Standards Institute (ANSI) regarding human–robot collaborative operations involve stopped-state monitoring, speed and separation, hand guiding, and power and force limiting. These characteristics are needed to be fulfilled for a robot to be called a collaborative robot. The absence of generalized and domain-specific safety standards further inhibits the capabilities of co-bots to operate at maximum speeds to realize faster production cycle time.

Compared with other industrial robots, collaborative robots lag behind in providing accurate solutions required in applications such as electronics assembly and healthcare operations. The repeatability (measured in a hundredth of an inch) offered by co-bots is in the range of +/−0.0039 inch (Universal Robots), which increases with higher payload, and is less compared with large-payload-capacity industrial robots. Small industrial robots without collaborative features and same payload capacity provide the same repeatability. With respect to the traditional way and analysis, the repeatability decreases with increase in payload; this increases the cycle time, especially in the case of critical tasks. This factor restricts the adoption of collaborative robots.

Please Explore Relevant Reports:

Industrial Robotics Market by Type (Articulated, Cartesian, SCARA, Parallel, Collaborative Robots), Industry (Automotive, Electrical & Electronics, Metals & Machinery, Pharmaceuticals & Cosmetics), and Geography – Global Forecast to 2023

Service Robotics Market by Operating Environment (Aerial, Ground, Marine), Application (Professional, Personal), and Geography (North America, Europe, Asia-Pacific, and Row) – Global Forecast to 2022

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