Cobots: The Future of Industrial Robotics in 2023 and Beyond

According to ISO 10218, from the International Organization for Standardization, there are four requirements for a robot to be termed as a cobot. Obliging to one or plurality of these requirements would enhance the safety of robot and position it as a collaborative robot (Cobot). The requirements are:

• Safety-rated monitored stop
• Hand guiding
• Speed and separation monitoring
• Power and force limiting

Cobots are equipped with software-controlled sensors that enable them to detect objects, people, and potential collisions to keep safety at paramount and end effectors like grippers for robotic manipulations. Furthermore, cobots also include:

• Sensors: Mounting a force/torque sensor on a robot arm makes the cobot more intelligent. With the help of the sensor during valve insertion, a robot will move to the direction where less force is felt. The capability of using the sense of touch expands the options for automation and allows companies to automate monotonous, repetitive work.
• Vision Systems: Vision systems are the eyes of cobots. Cameras and depth sensors capture visual data, enabling cobots to recognize objects, locate targets, and navigate autonomously. Machine vision algorithms analyze images, ensuring precise part recognition in manufacturing or assisting with pick-and-place tasks. This technology enhances cobots’ adaptability to diverse tasks and environments.
• Grippers: Grippers are cobots’ hands, and their design is critical for task versatility. Cobots can use various grippers, including vacuum, pneumatic, and adaptive grippers, to handle different objects. Adaptive grippers, with their ability to conform to object shapes, are especially useful for handling irregular items. Gripper technology advances enable cobots to grasp, manipulate, and release objects with precision, making them more versatile in applications such as assembly and material handling.
• Cobot Programming: Cobots are much easier to program as they don’t require specialized knowledge, eliminating the need for cost intensive robotic integration. This also cuts cobot deployment costs.

With drag-and-drop programming, users translate their actions into code, simplifying cobot programming. Just drag and drop actions in the right order to complete tasks. Some cobots allow users to sketch program layouts using buttons to guide the robot. Both methods are user-friendly, enabling more workers to interact effectively with the robot. Some cobot manufacturers go further, offering application wizards to simplify complex tasks, like configuring an end-of-line palletizing robot, reducing setup time.

Overall cobots offer user-friendly programming, adapt to various tasks, and lower upfront costs in industrials setting.

Some popular domains with end applications for cobots are detailed below:

• Manufacturing: Cobots help operators in manufacturing processes, such as welding, dispensing, assembly, or product inspection. They improve the quality, efficiency, and safety of the production lines, while reducing costs and waste. Exemplary companies that use cobots in manufacturing are BMW, Ford, Volkswagen, and Samsung.
• Logistics: Cobots assist workers in logistics tasks, such as picking and placing, packaging, or conveyance through a facility. They optimize the storage, distribution, and delivery of goods, while increasing the speed and accuracy of the operations. Exemplary companies that use cobots in logistics are Amazon, FedEx, DHL, and Walmart.
• Healthcare: Cobots support healthcare professionals in various services, such as surgery, rehabilitation, diagnosis, or patient care. Cobots can enhance the quality, accessibility, and affordability of healthcare delivery, while reducing the risks and errors. Exemplary companies that use cobots in healthcare are Intuitive Surgical, Medtronic, Hocoma, and Mabu.
• Education: Education is a new application for Cobots. Cobots can collaborate with human workers in educational activities, such as teaching, tutoring, mentoring, or research. In a world where virtual classrooms are gaining popularity, cobots can enrich the learning experience by acting as a moderator and physically representing the candidate who is sitting at a remote location. Thus, they can generate more interactive & personalized experience for the candidates. Some of the companies that are experimenting with cobots in education domain are SoftBank Robotics, Wonder Workshop, and RoboTutor.

Cobot developers & manufacturers keep on adding functionalities in form of new parts, highly accurate sensors, various data gathering & analysis means, improved working mechanisms, inclusion of AI & ML, data transmission, and communication to enhance the collaborative working and improve the operator safety. Following are some of the key advancements to watch:

• Perception sensors: Multiple sensor solutions enable perception capability of a Cobot to co-exist with human. Converging AI with perception sensors will be essential to enable Cobots to truly interact, anticipate, and communicate, especially when they need to hand off certain complex tasks to humans.
• AI & ML Integration: Having sensors is not enough. Making decisions by judging the behavior of a coworker is an essential requirement for safety & collaboration. The cobot must learn from the working pattern of various users before acting. In a world where collaborative working requires multiple users working on a single product/ task, robots also need to understand the worker behavior to ensure safety of each individual working in vicinity of the cobot. AI & ML come as a blessing here and ensure proper analysis of the environment. While the earlier robots would struggle to detect the working pattern of various users and would shut to prevent any harm, the new generation cobot can adapt with workers and keep working without sacrificing efficiency and productivity. 
• Cloud Computing & Connectivity: Industrial operations are of many kinds. For true automation and high productivity, a robot should learn from similar instances worldwide and adapt its working settings to ensure it can deliver the same output with least training. Thus, organizations are using cloud computing and connectivity. When similar tasks are done by cobots at various locations, the centralized repository of the data can be maintained at cloud and data can be shared with all participant cobots. Thus, learnings from one location can be quickly imitated at another location and the cobots can collaborate with high productivity. 
• Edge Computing & AI: Cobots need much closer control for real-time implementation of complex decisions in co-working environments. A lot of operations require making decisions on the end node where the data is generated and unaltered. These are unique situations which are not present on other sites and thus the decision making also needs to reflect the same attitude. That’s one area where edge computing comes in picture. Since the data gathering, analysis and response making is done at the edge node, the decision making is quick, more realistic, and highly effective.
• End-of-arm tooling: This is the most researched and worked field in cobots. The cobot industry cannot scale its operations if the cobots cannot be utilized for multiple purposes. In recent times, most of the research has been focused on identifying & developing the end-of-arm tools that can enhance the utility of cobots for various purposes. It includes designs of vacuum grippers, three finger grippers, magnetic grippers, pressure sensitive gripping mechanisms, EoAT with welding guns, etc.

These EoAT systems can handle a variety of materials with various shapes and properties. Further, the embedded sensors that allow the cobot to adapt its grip according to the object’s surface properties, material, and weight. The development of end-of-arm tooling plays a key role in the value a robot can bring to its end-user and will contribute highly to the wide adoption of industrial robots in new industries. New developments in EoAT are focused on advancing technology and adaptation of cobots.

Programming & Training enhancements: Cobot developers are also working toward enhancing the adaptability of cobots by providing cobots with voice recognition and analysis capabilities. Furthermore, there are developments happening in task mimicking, identifying and copying worker actions, understanding movements and acting etc., These new capabilities will enhance the utility of cobots and would limit the effort that is required in training cobots. More and more workers would be able to command cobots with movements and speech and it would further accelerate the adoption of cobots in various work environments.

According to various reports, the collaborative robot’s market’s revenue stood at approx. $1 billion in 2022, with shipments increasing by ~20% to ~40,000 units. Collaborative robots have also seen some growth due to pandemic and labor shortage. The cobot market is expected to grow at a rate of ~50% in the next 5 years. North America, Europe, China, Japan, and South Korea are the geographical regions that would support this growth. Specific countries that would experience rise in market share are U.S., Canada, Germany, France, U.K., Italy, Russia, China, Japan, South Korea, etc.

The unexpected focus and demand of the industry due to COVID, labor shortage, rise in cost of manual labor, etc., have fueled the need for collaborative robots. More and more industries are now adopting cobots and working toward a collaborative set-up.

In terms of the size of robots, payload becomes a criterion of evaluation. There are multiple kinds of cobots from payload capacity of 0-5kg to 15kg and more. Our analysis suggests that more than half of the total cobot market is dominated by cobots with payload size 5kg or less. Less than 10% of the total cobot market contains cobots with payload 15kg or more.

We have done a benchmarking study to compare some of the leading cobots for their specifications and prices. It includes payloads, DOF, reachability, ease of programming, type of rating, and popular applications that cobot is serving. The study also throws light on the fact that cobots with low payload are not expensive. The average price of a cobot with a payload of 0-5 kg is around $23,000. The price goes up as the payload increases, but the price increase is consistent. For example, the average price of a cobot with a payload of 5-10 kg is around $34,000, and the average price of a cobot with a payload of 10-15 kg is around $41,000.

The price of cobots varies according to the maker, functionality, technical features, and the end-of-arm tooling used. When considering the use of a cobot in manufacturing, an organization should determine the precise ROI that justifies the expense.

Cobots typically cost between $10,000 and $50,000 USD. When selecting a platform, the cobot’s manufacturing quality should also be considered because the additional tooling will increase the cost.

At FutureBridge, we have segregated and analyzed cobots companies into multiple categories including manufacturers, technology enablers (end effectors, software developers, vision and sensing system enablers), cobot transforming companies, automation and AGV enabling companies, Actuator and mechanism development companies, etc., Please get in touch for any further information.