Robots and Artificial Intelligence: Revolutionizing Business for the Better
The idea of robots powered by AI has fascinated and ignited imagination for decades. Today, robotics ideas that were once science fiction are a reality for many businesses.
Companies are using AI-powered robots to bring humans and technology closer together, solve problems, and transform their business models to meet changing demands.
For example, AI-enabled robots greet customers in stores and provide personalized information and directions. They harvest ripe vegetables in farm fields and serve made-to-order lattes in coffee shops. In industrial settings, AI-enabled robots keep workers safe by operating in shared spaces and handling dangerous tasks. They also perform complex tasks such as independently cutting, grinding, welding, and inspecting. In healthcare, robotics can assist in precise surgical procedures.
What Are AI-Powered Robots?
AI-powered robots have the ability to collect, analyze, and act on information about their surroundings in near real-time to complete tasks, often autonomously.
Robots use cameras, accelerometers, and sensors for vibration, proximity, and other conditions to collect information about their environment. Depending on the use case, that data is then analyzed using onboard, edge, or cloud computing—or some combination—and machine learning or deep learning algorithms. The robot then uses insights from that analysis to take action.
To better understand what AI-enabled robots are, it’s important to understand what makes them intelligent.
Artificial intelligence refers to a broad class of systems that enable machines to mimic advanced human capabilities. Machine learning enables machines to learn from data to make predictions or decisions. Deep learning enables machines to use data to determine actions and perform tasks independently.
Benefits of Integrating AI
Organizations gain many benefits from integrating AI-enabled robots into their operations.
Increased Productivity and Efficiency
Companies today are juggling more demands than ever before. Customers want faster delivery. Stakeholders want higher productivity and increased efficiency. And workers want to contribute without fatigue or injury. AI robots are helping on all fronts. In retail environments, for example, robots perform repetitive or time-consuming tasks, such as checking inventory and alerting staff to out-of-stock or misplaced items. This expedites product delivery, improves productivity, and frees human workers to spend more time supporting customers.
Improved Quality and Accuracy
AI robots can see and understand their environments, which enables them to complete complex tasks such as quality-control inspections on assembly lines. In industrial applications, AI robots can check the quality of goods in line instead of delaying the task until the end of the process, saving the manufacturer time and money.
Enhanced Worker Safety
AI robots play a major role in improving workplace safety. Companies in the oil and gas sector often use robots to perform data collection or safety inspection tasks in dangerous environments to reduce risk to humans. Additionally, because AI-enabled robots can learn from human gestures and speech, they can continuously improve their ability to complete tasks while safely working alongside employees.
AI Robot Capabilities
A common misconception about robots augmented with AI is that they will begin to act freely or in a way that is beyond the scope of their original task. However, robot intelligence is not the same as human intelligence. Robots cannot create new abilities outside the scope of what they were programmed to do.
Another popular misconception is that AI-powered robots will replace humans in all jobs. Robots augmented with AI will likely transform jobs by improving efficiency, productivity, and safety. As a result, humans can focus on higher-value, strategic, or relationship-building activities.
To make a robot truly intelligent, several critical technology-supported capabilities are required.
Robotics and Machine Learning
Machine learning is critical to an AI-enabled robot’s ability to learn and progressively improve task execution. Machine learning enables robots to use real-time data and contextual information acquired through their experiences to develop new learning pathways and capabilities. This allows these robots to solve new and unique problems as they encounter them in their environments.
Natural Language Processing
Natural language processing (NLP) is a type of artificial intelligence that enables a robot to understand human language as it is spoken. AI robots with NLP typically complete tasks that involve:
- Answering questions posed by humans.
- Recognizing and interpreting speech.
- Analyzing the sentiment and intention of spoken language.
In retail, healthcare, and hospitality, NLP enables AI robots to directly interface with customers at touchless kiosks, serve as virtual assistants in banks to minimize human-to-human contact, or entertain residents in retirement communities.
Conversational AI
Conversational AI, or generative AI (GenAI), uses data, NLP, and machine learning to take an AI robot’s interaction capabilities with humans to the next level. Using conversational AI with AMRs or humanoid robots aims to offer more human-like interactions between people and computers. With every interaction, the robot will capture dialogue, process it, respond, and learn in anticipation of the next interaction. For example, SM Supermalls, a chain of shopping malls in the Philippines, is streamlining and improving the visitor experience with a fleet of voice-interactive, smart service robots.
Types of Robots
When augmented with AI, robots can help businesses innovate and transform their operations. Following are some of today’s most common types of robots powered by AI.
Autonomous Mobile Robots (AMRs)
As AMRs move through their environments, AI enables them to:
- Capture information through 3D cameras and LiDAR sensors.
- Analyze the gathered information.
- Make inferences based on their environment and overall mission.
- Move or act to deliver the best outcome.
Depending on the industry, the tasks and actions completed by AI-empowered AMRs vary widely. For example, when moving inventory from one point to another in a warehouse, AMRs can avoid collisions by navigating around human workers or fallen boxes while simultaneously determining the optimal path for task completion.
Humanoids
While many mobile humanoid—or service—robots may technically fall under the domain of an AMR, the term is used to identify robots that perform human-centric functions and often take human-like forms. These robots use many of the same technology components as AMRs to sense, plan, and act as they carry out tasks such as providing directions or offering concierge services.
Articulated Robots
Articulated robots, also known as robotic arms, are meant to emulate the functions of a human arm. AI allows articulated robots to perform tasks faster and more accurately than humans. AI technologies infer information from vision sensors, such as 2D/3D cameras, to segment and understand scenes and detect and classify objects.
Cobots
AI enables cobots, or collaborative or companion robots, to respond to and learn from direct human-robot interactions, including human speech and gestures, without worker-assisted training. Cobots function alongside humans, so they move slower than traditional robots to preserve human safety. Additionally, cobots are designed to handle lighter tasks than traditional robots built for more demanding jobs like large-scale manufacturing.
Hybrids
The various types of robots are often combined to create hybrid solutions capable of more complex tasks. For example, an AMR might be combined with a robotic arm to create a robot for handling packages inside a warehouse. As more functionality is combined into single solutions, compute capabilities are also consolidated.
AI in Robotics Use Cases
Enterprises are investing in AI to automate processes, personalize customer and employee experiences, and transform their industries. AI-enabled robots are being deployed to enhance outcomes, such as quality, productivity, and cost savings while reducing the burden on employees so they can focus on the most critical and highest-value tasks. The following are just a few of the many industry uses of AI-enabled robots.
Manufacturing
The manufacturing industry has long been at the forefront of using robots. AI-enabled AMRs, automated guided vehicles (AGVs), articulated robots, and cobots are deployed on factory floors and in warehouses to help expedite processes, drive efficiency, and promote safety. They’re used across a variety of applications, including welding, assembly, materials transportation, and warehouse security, and often handle dirty, repetitive, or dangerous tasks to improve human safety and productivity.
Farming and Agriculture
AMRs are helping farmers harvest crops more quickly and efficiently. Autonomous tractors and harvesters use GPS, sensors, and AI to perform tasks like plowing, planting, and harvesting with minimal human intervention. AI-enabled agricultural robots assess ripeness and pick the crop precisely and delicately to avoid harming the product. Drones monitor crops, spray pesticides, plant seeds, and provide real-time data to farmers. Robotic weeders can identify and remove weeds, reducing the need for chemical herbicides.
Healthcare
Various types of robots are used in the healthcare industry to enhance the patient experience. AMRs are used to deliver medication, disinfect surfaces, or provide mobile telepresence functionality. Cobots are used to assist medical professionals during rehabilitation, for medication delivery and patient monitoring, and to help nurses better support their patients.
Retail and Hospitality
Robotics can enhance customer or guest experiences in various ways. Retail and hospitality businesses use robots to greet customers, provide concierge or way-finding services, complete janitorial services, and assist customers with luggage. Robots equipped with cameras and sensors use computer vision capabilities to scan shelves to monitor stock levels and identify misplaced items to automate inventory processes. Service robots support hospitality functions in tasks like room service delivery, cleaning, and even in kitchens to prepare food, ensuring consistency and hygiene.
The Future of AI and Robotics
Modern robots, unlike their isolated stand-alone predecessors, tap into cloud and edge computing and AI to continuously learn and adapt. Rapid technological advancements are unlocking new robotic capabilities and use cases in unprecedented ways.
Three exciting trends in AI and robotics:
- Cloud robotics, which would allow robots to cost-effectively learn by sharing experiences with other robots.
- Progressions in deep learning that will allow robots to generalize their perceptions based on data associations to emulate human memory.
- Developing neuromorphic (brain-inspired) hardware to provide more computing performance while consuming less power.
AI-enabled robots will likely evolve to learn autonomously by grouping similar experiences, receiving feedback from their environments—also called reinforcement learning—and running simulations to solve problems without physical action. Unlike humans who learn gradually, networked robots could instantly share and build upon collective knowledge, with improvements to one system benefiting all others.
Widespread high-speed wireless connectivity is enabling near real-time communications with robots, while sensors and actuators, or the elements that convert energy into action, are becoming more collaborative. In parallel, embedded processors are increasing control complexity, performance, and reliability for command response and power management systems. Altogether, these advancements will quickly make robots more competent and efficient. However, while robot capabilities are increasing exponentially, they will always require human-provided information for optimal operation.