A robot is an artificial agent capable of taking actions in the real world. Implemented with computer hardware and software, it often has physical manifestations and uses AI for tasks like navigation, perception, and manipulation.


Imagine that when you’re playing with your remote-control car, the car doesn’t need you to control it. The car now moves around, avoids hitting walls, and can even pick up and bring your toys back to you. That’s what a robot can do.

In-depth explanation

Robots are machines designed to perform tasks with minimum human intervention. They are an intersection of hardware (physical components) and software (programs). Unlike traditional machines, robots use sensors and processors to interact with their environment, hence resembling autonomous entities.

In the context of AI, robots often use Machine Learning (ML) algorithms to learn from their environment, and make decisions or predictions based on this acquired data. This learning can be supervised (when they have a known dataset to learn from) or unsupervised (when they discover patterns themselves). Reinforcement learning, a type of ML, is particularly common: a robot tries several strategies and favors those producing the most ‘reward’.

Robots can feature various degrees of autonomy. A fully autonomous robot can initiate actions, monitor, and alter its activities to optimize its tasks. Semi-autonomous robots can perform certain tasks on their own but need human intervention for more complex instructions.

A robot’s physical layout can be humanoid-type (resembling a human body), mobile (wheeled or non-wheeled), or stationary. A perfect example is the Mars Rover, which uses sophisticated ML algorithms to navigate and analyze geological samples.

Control architectures for robots usually fall into three categories: deliberative, reactive, and hybrid. Deliberative architectures are plan-driven, while reactive ones are more spontaneous and respond to immediate changes in their environment. Hybrid architectures aim to balance between long-term planning and reaction to immediate circumstances.

Robots can be used in diverse industries such as manufacturing (to automate processes), healthcare (surgical robots, patient care), space exploration, agriculture (automated tractors), and entertainment (gaming bots).

Machine Learning, Reinforcement learning, Supervised learning, Unsupervised learning, Autonomous Systems, Computer Vision, Control Architectures, Perception, Manipulation