Skip to content

The Data Scientist

the data scientist logo

6 Biggest Challenges in Robotics

Wanna become a data scientist within 3 months, and get a job? Then you need to check this out !

The journal Scientific Robotics surveyed to identify some of the biggest challenges robotics faces. Although it’s very difficult to pinpoint every challenge, the panel identified the most important ones in hopes that technological breakthroughs in the future will likely be able to address them. Interestingly, most of these challenges are faced by the surrounding technology that enables robotics like artificial intelligence, 5G, the Internet of Things (IoT), etc.

One thing is for sure robotics isn’t going anywhere and we can only expect an increase in its adoption as it continues to contribute to multiple sectors. If you’re thinking about getting into robotics, now is an excellent time, and it’s easier than ever to get started. All you need is a good internet connection like CenturyLink Internet to utilize online resources without any lags and interruptions. Here are the bottlenecks the robotics industry is currently facing.

1. New materials, fabrication methods

Yes, we’re seeing more and more robots made of different materials, and the fabrication methods for each type also vary. However, there’s more untapped potential, especially with the uptake of synthetic materials like artificial muscles that are helping with soft robotics, and assembly targets.

2. Cost

As the demand for industrial robotics is increasing because of automation, the cost is becoming a deal breaker for some businesses. Yes, automation can do some jobs faster than humans could, but the initial high price point is acting as a barrier to its adoption. The whole point of adopting robotics is to increase efficiency while also lowering costs.

Mass adoption of robotics can lead to lower costs in most cases. Similarly, manufacturing companies can use cost-effective materials in the production of these industrial robots. Moreover, they can implement automation in the manufacturing process of these robotics to minimize the cost of production, which will in turn reduce the final cost.

Modular robots are becoming increasingly popular that allow you to assemble the robot yourself by following a simple guide. This lowers the assembly cost on the manufacturing end and the relief is passed on to the consumer.

3. Complexity

Robots are complex machines made of many parts, and it’s not just the hardware. Robotics manufacturers have to create complex programs for the machine to do a task, which might sound easy but can get very time-consuming if you have to do it for each task. Additionally, robots need a lot of components to properly function.

For example, a robot will need to have a ton of sensors to read the environment and gauge its response, actuators to move its limbs, and a controller to act as its brain. On the software side of things, they’ll need a fully functional piece of code to instruct them on how to perform a task. All this complexity can sometimes work against them as it can lead to a potential failure of one or more components.

4. AI that can reason

It’s very hard for someone to accurately predict all the possible scenarios a robot is going to be in. Sure, you can feed it a program for a task, but how many pieces of a program can an individual or a team write for a robot to be sufficiently self-reliant? The world is moving towards AI and newer machine learning algorithms are constantly being developed.

The end goal is to make autonomous robots that can independently take decisions in different situations based on the data they gather as humans do. However, it’s a double-edged sword. On the one hand, autonomous robots will significantly add to our lives as they’ll be able to do more difficult and dangerous jobs instead of humans, thus saving precious human lives. On the other hand, these autonomous robots could replace a lot of the human workforce as they’re not limited by physical needs, unlike humans.

5. Communication

Communication is another pain point when it comes to robotics as robots need to be able to effectively communicate with each other, humans, and other non-living objects to function properly. All of these communication modes use different mediums. For example, robots would communicate with other robots wirelessly but need voice and texts to communicate with humans. Similarly, they would need actuators and sensors to communicate with other machines and objects.

6. The regulations surrounding robotics

As more robots are being developed in different parts of the world, the need for a standardized set of regulations is imminent. Moreover, this industry is in its developmental stage and the regulatory structure needs to keep up to reflect the latest developments. Another thing of note is that not all robots need the same set of rules to operate.

For example, a robot vacuum cleaner is subject to a different set of regulations than a robot working in the healthcare sector.


Admittedly, the robotics industry is facing huge challenges that need to be addressed on a priority basis, but the potential benefits are also vast. If robots are made more affordable and accessible, more intelligent, and the complexity is also handled correctly, our lives could greatly benefit from them. Lastly, the need for a thorough regulatory structure that is dynamic and takes into account the latest developments is the need of the hour.

If you’re passionate about robotics and want to dive deeper into this exciting field, consider exploring our data science courses.

Our courses will equip you with the knowledge and skills to tackle the challenges mentioned in this article and contribute to the advancement of robotics. From learning about new materials and fabrication methods to understanding AI and communication in robotics, our courses offer comprehensive training to help you excel in this rapidly evolving field.

Don’t miss out on the opportunity to be at the forefront of robotics innovation. Visit our website to learn more about our data science courses today.

Wanna become a data scientist within 3 months, and get a job? Then you need to check this out !