Robotics isn’t just one subject, it’s a mashup of many. Think of a robot as a miniature world where mechanical parts, electrical signals, software algorithms, and even human-like decisions work together to bring something to life. To build a working robot, you don’t just need one kind of knowledge you need a team of disciplines talking to each other, just like the parts of the robot itself.

At its core, robotics brings together mechanical engineering (for structure and motion), electrical engineering (for circuits and power), and computer science (for programming and control). But that’s just the beginning. As robots get smarter, they also need AI and machine learning for perception and decision-making, control theory for movement precision, and even UX design when interacting with humans. Without these individual disciplines syncing together, robots would just be boxes of metal and wires – fascinating, but not functional.

So why should you care about all these disciplines? Because robotics is where theory meets the real world. You might write the perfect algorithm, but if the motors don’t work or the sensors give noisy data, your robot will fail. That’s why roboticists often wear many hats or at least know how to speak the language of different fields. In this blog, we’ll break down the major disciplines that make robots tick and show you how they all come together to build machines that sense, think, and act. So let us dive deep into the disciplines that shape robotics.

Mechanical Engineering

Mechanical engineering is what shapes the structure, movement, and mechanics of robots. This includes everything from joints, arms, and wheels to complex grippers and chassis designs. Mechanical engineers in robotics handle material selection, kinematics, dynamics, CAD Design, actuator design and selection, as well as performing structural analyses.

Mechanical engineers ensure the robot has the right physical design and structure, choosing materials like lightweight aluminum or durable composites, and making sure it can withstand the forces it will encounter. Imagine designing a healthcare robot like Baymax from the movie Big Hero 6! A mechanical engineer has to design not only the internal framework and the chassis that makes up the robot, but also decide what material is needed to make the robot serve its purpose. Which in case of Baymax, is being cuddly and huggable, and interacting with humans.

All of this is first 3D modelled by our big hero mechanical engineer using CAD software like Fusion360 or SolidWorks. Load and stress analyses are conducted using simulation software like Ansys. Design parameters like dimensions, materials, and features like fillets, and chamfers are modified in different iterations until we have the desired body for our robot. Apart from this, the mechanical engineer also has to select or design actuators and grippers. Actuators (motors, hydraulics, pneumatics) provide the power for movement, while grippers (or end-effectors) are designed to pick up, manipulate, or interact with objects. Mechanical engineers ensure these components are powerful enough, precise, and integrated seamlessly into the robot’s structure.

The task of the mechanical engineer does not end here! Once the body has been designed, and the actuators and grippers selected, they also need to study how the robot will move in space and how the commands given to the motor will affect the motion of the robot in physical space. This is done using kinematics and dynamics. Kinematics describes motion without regard for the forces causing it, focusing on position, velocity, and acceleration, while dynamics studies the relationship between forces and motion, explaining why objects move the way they do. Forward kinematics calculates the position and orientation of the end-effector (e.g., hand or tool) given the joint angles. Inverse kinematics, on the other hand, determines the joint angles needed to achieve a desired end-effector position and orientation. Similarly, dynamics may also be forward or inverse. In Forward Dynamics, given forces and torques, the resulting motion (joint angles, velocities, accelerations) is predicted. Inverse Dynamics on the other hand, determines the forces and torques required to produce a motion, given the motion (joint angles, velocities, accelerations).

In the context of our big fluffy hero Baymax, this means that the body is designed using CAD software, design parameters are analyzed and optimized, and an appropriate manufacturing process is selected to turn the digital twin into a physical body. Then, actuators such as motors or hydraulic actuators are chosen and added to our robot (this could be many little servo motors for the hands and legs of our robot). For Baymax, the materials would need to balance durability with softness, likely combining an inflatable outer shell with a lightweight but sturdy internal frame.

The actuators must provide smooth, controlled movements that make him seem approachable and safe for interacting with humans, especially in a healthcare setting. Baymax needs to move in a way that feels natural and gentle. This is where kinematics and dynamics come in. Kinematic analysis helps determine how his joints should move to reach out for a handshake or a hug, while dynamic analysis ensures that the forces generated during those movements don’t destabilize him or make his actions feel robotic or jerky. Through careful study of motion and forces, mechanical engineers can make sure Baymax not only looks friendly but moves like a caring, helpful companion too.

(Psst! Carnegie Melon is building a real-life Baymax in a project called ‘Build Baymax’. Check it out here.)

Electrical Engineering

If mechanical engineering provides the body, electrical engineering gives the robot its energy and nervous system. This is the discipline responsible for all the circuits, power systems, signal processing, and embedded systems that allow a robot to sense its surroundings, process information, and execute tasks. While the mechanical structure forms the skeleton and muscles of a robot, electrical engineering forms its heartbeat, neural network, and reflexes, bringing life to an otherwise static frame.

At the heart of this discipline is PCB (Printed Circuit Board) Design. Electrical engineers create the custom circuit boards that connect and control all the essential electronic components of the robot. These boards house microcontrollers, interface circuits for sensors and actuators, motor drivers, and communication interfaces. A well-designed PCB is compact, efficient, and tailored precisely to the needs of the specific robot, reducing the complexity of wiring and improving reliability.

The power system manages how energy flows through the robot. This involves selecting and designing appropriate batteries for mobile robots like drones or service robots, or fixed power supplies for larger, stationary robots. Electrical engineers ensure that each component (sensors, motors, processors) receives the correct voltage and current, while also monitoring overall energy consumption to optimize efficiency. Imagine Baymax: he might look soft and fluffy on the outside, but hidden inside would be carefully designed circuits that distribute power to his various systems, ensuring that his arms don’t run out of juice while he’s giving a hug!

Another key area is signal processing, which involves filtering, amplifying, and interpreting the raw data coming from sensors. Sensors like IMUs (Inertial Measurement Units), encoders, microphones, or even temperature sensors constantly produce noisy data. Electrical engineers use signal conditioning techniques, like filtering or analog-to-digital conversion, to make sure that only meaningful, reliable data reaches the robot’s brain for further processing.

Next comes embedded systems. This involves programming the robot’s onboard microcontrollers. These are small, specialized computers like Arduino, STM32, or ESP32. These microcontrollers act as the local “brains” of the robot, handling real-time tasks like reading sensor inputs, controlling motor drivers, or managing wireless communication. Without embedded systems, higher-level computing platforms would be overloaded trying to handle everything from low-level motor commands to complex path planning.

Of course, a robot needs to sense its surroundings to interact meaningfully with the world. Electrical engineers play a key role in sensor integration. This involves choosing, connecting, and calibrating sensors such as cameras for vision, LiDAR for mapping, ultrasonic sensors for obstacle detection, or force sensors for delicate manipulation. Selecting the right sensors, placing them optimally, and ensuring they provide reliable data is one of the major responsibilities of the electrical engineering team.

Finally, motor control ties it all together. Developing the circuits and controllers that govern a motor’s speed, torque, and position is essential for ensuring that a robot moves smoothly and accurately. Pulse Width Modulation (PWM), feedback control using encoders, and advanced motor driver circuits allow for precise control of motion. Without this, the robot’s movements would be jerky or imprecise, limiting its functionality.

All these aspects of electrical engineering come together in complex robots like Baymax from Big Hero 6. While his soft, inflatable exterior is the work of mechanical engineering, his ability to sense a person’s presence, interpret voice commands, and carry out complex actions depends entirely on electrical systems. His power system would need to be carefully designed to keep his processors, sensors, and motors running efficiently. Embedded microcontrollers would handle his gestures and responses in real time, while signal processing would make sure that voice inputs and sensor readings are reliable. Motor control circuits would govern his smooth and friendly movements. Without robust electrical design, Baymax would just be an inflatable statue—electrical engineering gives him the life, awareness, and responsiveness that make him a healthcare companion rather than just a mechanical toy.

In short, while mechanical engineers give a robot its form, electrical engineers give it the life to move, sense, and interact with its environment. Without robust electrical design—clean, reliable power; well-integrated sensors; and efficient embedded systems—even the most elegant mechanical structure would remain motionless

3. Computer Science & Software Engineering

Computer science and software engineering play a major role in robotics by giving robots the ability to make decisions and perform complex tasks. Hardware of the robot can only do what it is told; software provides the instructions, and the ability to adapt, learn, and perform complicated tasks. From writing control logic to planning motion paths and analyzing sensor data, it’s the most versatile discipline in robotics.

Computer science in robotics is about writing the logic that makes the robot behave intelligently.From interpreting complex sensor data to making decisions about where to go next, software bridges the gap between raw data and purposeful action.

One of the key pillars here is algorithms and data structures. Robots operate in real-time environments and must make decisions quickly. Efficient algorithms help them decide what to do and when to do it. Classic algorithms like A*, Dijkstra’s, or RRT (Rapidly-exploring Random Trees) are used to help robots plan paths through complex environments. Meanwhile, data structures like graphs represent maps, queues handle streams of sensor data, and trees power decision-making processes.

Modern robotics also relies heavily on frameworks like the Robot Operating System (ROS), which acts as the glue between the robot’s hardware and the sophisticated algorithms written by developers. ROS breaks down the robot’s brain into manageable pieces: perception, control, planning, and communication, all working together through a publish-subscribe system. Without ROS or similar systems, coordinating complex robotic tasks would be nearly impossible.

A particularly fascinating application of computer science in robotics is SLAM (Simultaneous Localization and Mapping). Imagine placing a robot in an unknown room with no map and asking it to explore, find objects, or exit safely. SLAM allows the robot to build a map of its environment while simultaneously figuring out where it is within that map. It’s like asking someone to draw a map of a maze while walking through it blindfolded, using only touch and hearing. Once the map is built, path planning algorithms help the robot decide how to reach its goal while avoiding obstacles.

Another important aspect of computer science in robotics today is Artificial Intelligence (AI) and Machine Learning (ML). While traditional algorithms tell robots exactly what to do in predictable situations, AI gives robots the ability to learn from experience, recognize patterns, and adapt to new environments. For example, computer vision algorithms help robots identify objects, people, or obstacles using camera data, while machine learning models help them improve over time by learning from mistakes or successes. Not only this

In the world of Baymax, all of these systems would work together to help him navigate through a hospital, analyze patient data, or respond to spoken commands. While mechanical and electrical engineering make his body move, it’s the software that would help him decide what to do next.

In short, computer science transforms mechanical potential into intelligent behavior, allowing robots to learn, adapt, and solve problems on their own. Without it, a robot is just a collection of silent motors and circuits with no direction or purpose.

Control Engineering

Just telling a robot to move isn’t enough. It needs to move precisely, smoothly, and safely, whether it’s a robot arm placing components on a circuit board or a drone hovering steadily in midair. Control engineering specializes in designing feedback loops and mathematical models to help robots perform tasks reliably, even in changing environments.

The most common foundation of control systems is the PID controller (Proportional-Integral-Derivative controller). It works by constantly comparing the robot’s current state, like position or speed, with the desired value. Whenever there’s an error between them, the PID controller quickly calculates how to correct that error by adjusting motor outputs. Without PID, your self-balancing robot or drone would either overcorrect and oscillate wildly or fail to react quickly enough to stay upright. It minimizes the present error, dampens oscillations, and eliminates steady-state error.

Beyond PID, control engineers often use state-space modeling, which involves representing the robot’s behavior using advanced mathematical equations. This allows engineers to predict future movements, handle multiple variables at once, and design controllers for more complex systems, especially in high-performance robots or autonomous vehicles. An example of a state-space-based control method is the Linear Quadratic Regulator.

One of the most important responsibilities of control engineering is ensuring stability and robustness. Stability means that the robot doesn’t spiral into uncontrolled motion after a small disturbance, like someone gently nudging a balancing robot or a drone encountering a gust of wind. Robustness means that even if the model isn’t perfect or if there are external disturbances, the control system will still work reliably.

Control engineers also work closely with modeling and simulation. Before implementing a control strategy on the real robot, they build mathematical models of the system and test them using simulation tools. This helps predict how the robot will behave in different scenarios and minimizes the risk of failure when testing with physical hardware.

To bring this into perspective, imagine Baymax gently reaching out to catch a falling object. While mechanical and electrical engineers build the arm and wire the circuits, control engineers ensure that Baymax’s hand moves to exactly the right position at exactly the right speed without dropping or crushing the object. Feedback control ensures that his sensors keep monitoring his actual position in real time and correct any errors before they become noticeable.

In short, control engineering is what transforms raw mechanical and electrical power into purposeful, accurate, and intelligent motion. Without well-designed control systems, robots would be unstable, imprecise, or even dangerous.

Mathematics & Physics – The Foundation

BBeneath every gear, circuit, and line of code, mathematics and physics form the true foundation of robotics. Every robot—no matter how advanced—is guided by the rules of math and the laws of physics.

Mathematics provides the language for describing movement, shape, and uncertainty. Linear algebra is used to rotate and translate objects in 3D space, helping the robot understand where things are. Calculus describes how things change over time, crucial in trajectory planning or control loops. Probability and statistics help robots make sense of noisy sensor data and make educated guesses about what’s happening around them, especially in uncertain environments.

Meanwhile, physics explains how forces, torques, and energy interact in the real world. Without a grounding in Newton’s laws or an understanding of friction and inertia, even the best-designed robot might slip, fall, or waste energy.

Even if your robot isn’t solving equations in real time, you, as the designer or programmer, rely on this mathematical and physical understanding to make sure your creation behaves as expected in the real world.

Without math and physics, everything else—mechanical parts, electrical systems, computer code—would simply float around with no rules to hold them together.

Other Disciplines – Completing the Picture

While mechanical, electrical, and computer science form the technical backbone of robotics, building truly useful and meaningful robots requires contributions from many other fields as well.

Cognitive Science & Psychology play a critical role in shaping how robots interact with people. As robots leave factories and enter our homes, hospitals, and public spaces, they need to be not only functional but also understandable, safe, and comfortable to be around. Understanding human expectations, communication patterns, and emotional responses helps robots become companions, not just machines.

Closely related to this is User Interface (UI) and User Experience (UX) Design. Whether it’s a touchscreen control panel, a companion app, or voice interactions, good UI/UX ensures humans can interact with robots intuitively and confidently.

Even fields like industrial design help shape the appearance of robots to inspire trust or friendliness, especially for social robots or those used in sensitive environments like healthcare or education.

Ethics and Philosophy also come into play, especially when designing robots that make autonomous decisions or interact closely with vulnerable populations.

The Future: A Collaborative Canvas

The true marvel of robotics isn’t found in any single discipline, but in its powerful synergy. Creating a truly capable robot is a team sport, demanding seamless collaboration and continuous innovation across these diverse fields. As robotics continues its breathtaking march forward, we’ll see even deeper integration, new specializations emerging, and perhaps entirely new disciplines born from this exciting convergence.

The next time you see a robot, whether it’s a factory arm or a delivery drone, take a moment to appreciate the incredible “symphony” of disciplines that brought it to life. It’s a powerful testament to human ingenuity and the boundless potential of collaborative innovation.