A robotics AI company is a company that specializes in the intersection of robotics and artificial intelligence (AI). It acts as a bridge between these two rapidly evolving fields. Its team of engineers, developers, and data scientists work together to create robotic AI technologies that can streamline workflows, automate tasks, and enhance customer service.
Robotics AI can be categorized into two main aspects — by robot body type and by AI functionality:
By robot body type:
- Industrial robots
Fixed robots with high precision and repeatability, commonly used in manufacturing for tasks like welding, assembly, and painting. With AI, these robots could focus on optimizing movements, performing quality control checks through vision systems, or adapting to slight variations in production processes.
- Collaborative robots (cobots)
Designed to work safely alongside humans, cobots are often smaller, more flexible, and easier to program than industrial robots. AI in cobots might involve features like collision avoidance, human-robot interaction, or object recognition to assist with tasks.
- Mobile robots
Able to move around autonomously or with some guidance, they are used in various applications, such as warehouse automation, floor cleaning, or delivery services. AI in mobile robots plays a crucial role in navigation, obstacle avoidance, path planning, and potentially interacting with their environment.
- Humanoid robots
Resemble the human form and are designed to interact with the world in a human-like way. AI in humanoid robots is complex, requiring advanced capabilities in areas like computer vision, motion control, and natural language processing. These robots are still under development but can potentially be used in healthcare, customer service, or search and rescue.
By AI functionality:
- Pre-programmed AI
Also known as rule-based AI, it takes a foundational approach used in many robots today. It explicitly instructs the robot on how to perform a specific task through a set of pre-defined rules and instructions.
- Machine learning
Robots with machine learning can learn and improve their performance based on data they collect over time. This allows them to adapt to changing environments or handle unforeseen situations.
- Deep learning
This advanced form of AI enables robots to learn complex patterns and relationships from large datasets. This can be used for tasks like object recognition, image classification, or even natural language processing for more interactive robots.
The global market for AI robotics is projected to grow to a market value of $64.35 billion by 2030. This surge in demand can be attributed to the continuous transition of industries into digitalization and machine learning. Another key driver of robotics AI is automation, which can improve productivity in workplaces and increase accuracy.
In some regions, labor costs are steadily rising, making automation through robotics AI a more attractive option for companies that want to maintain competitiveness.
Success story
One example is the case study of Zenni Optical, an online retailer known for its customizable eyeglasses. It struggled to keep up with order fulfillment due to slow and error-prone manual picking in its warehouse. Traditional robotic solutions were deemed unsuitable for handling the variety and fragility of its products, which pushed Zenni Optical’s team to reach out to OSARO.
OSARO’s robots have computer vision with machine learning and can identify and grasp different types of eyeglasses. Its robotic system is equipped with custom end-effectors designed for safe and precise handling. The AI also integrates with existing warehouse management systems, bagging equipment, and sensors for a seamless workflow.
Its AI-powered robotic system significantly improved Zenni Optical’s order fulfillment process. Picking speed increased, leading to faster delivery times and improved customer satisfaction. Additionally, the AI’s ability to learn and adapt minimized errors compared to manual picking.
As a result, Zenni Optical achieved the following:
- 80% increase in throughput
- 50% boost in productivity
- 99.9% order processing accuracy
- Label up to 410 eyeglasses an hour
Proposals