A free place to start learning robotics. Try short interactive concepts, read practical handouts, and follow a roadmap from your first circuit to a robot that maps and navigates on its own.
Maintained by Prof. Xian (Shawn) Li, Department of Electrical and Computer Engineering, Northeastern University.
Almost every robot, from a vacuum to a Mars rover, runs the same loop many times per second. It senses, it thinks, and it acts. Each concept on this site is one piece of that loop.
Measure the world and the robot itself, with wheel encoders, IMUs, cameras, and LiDAR.
Work out where the robot is and what to do next, even when every sensor is noisy.
Turn a decision into motion, through wheels, motors, and joints.
Acting changes the world, so the robot senses again, and the loop repeats.
Short interactive pages that show one robotics idea at a time. Move the sliders and watch what changes.
Sort everyday machines into robot and not robot, and see what sensing, thinking, and acting each add.
Run a robot loop one tick at a time and see how the loop rate decides whether the robot stops before a wall.
Build simple mechanisms, count links and joints, and see how many independent ways each one can move.
Wire two light sensors to two wheels in four ways and watch fear, aggression, love, and curiosity appear from simple wiring.
Tune a two-sensor and a five-sensor line follower on a curved track and compare on-off control with proportional control.
Watch Bug 1 and Bug 2 reach a goal around unknown obstacles using only a touch sensor and the direction to the goal.
Stack avoid, seek, and wander behaviors and see which layer takes control at each moment.
Drag two vectors and watch the projection, angle, and cross product update, then use them to tell if a target is ahead or to the left.
Move and rotate a robot frame inside a world frame, and see how a point seen by the robot maps to world coordinates.
Rotate a 3D frame about x, y, and z and see that changing the order of the same rotations gives a different result.
Turn the yaw, pitch, and roll rings of a gimbal until two of them line up and one degree of freedom disappears.
Pick a rotation axis and an angle and watch a vector sweep around the axis, then see the rotation matrix from Rodrigues' formula.
Blend between two orientations with slerp and with naive Euler-angle blending, and compare the paths the nose takes.
Chain world, base, arm, and camera frames and follow a point seen by the camera through every transform to the world.
Pick any end pose for a rigid body and see that the motion is a single rotation about one fixed point, the planar version of a screw axis.
Drive a robot with heading noise and see why its uncertainty is a banana, not an ellipse, and how the Lie group exponential map captures it.
Drag noisy points, fit a line or curve, and see the squared residuals the fit makes as small as possible.
Fit a curve with Gauss-Newton and Levenberg-Marquardt from the same start, and watch where Gauss-Newton overshoots and LM stays safe.
Drop a ball on a cost surface, change the step size until it diverges, and see how momentum helps in a narrow valley.
Stretch and rotate a 2D Gaussian and see the 1, 2, and 3 sigma ellipses and how many samples fall inside each.
A robot checks whether a door is open with a noisy sensor. See how each reading updates its belief, drawn as areas you can see.
Estimate the free area of a cluttered room by throwing random points, and watch the error shrink as more points land.
Simulate the same pendulum with three integrators and see Euler gain energy while RK4 stays accurate.
Film a spinning wheel at different frame rates and see it appear to slow down, stop, or turn backward.
Build a sensor signal from sine waves and noise, see its spectrum, and remove the noise with a low-pass cutoff.
Change a battery and a resistor and watch current and power update in a circuit, then add an LED and see why it needs a resistor.
Read a light sensor through a voltage divider, then see why a button input with no pull-up resistor reads random values.
Sample a sensor voltage at different bit depths and see the quantization steps, the error they leave, and clipping past the reference voltage.
Switch the four transistors of an H-bridge to drive a motor forward, backward, or to a stop, and set its speed with the PWM duty cycle.
Count encoder pulses with a polling loop and with an interrupt, and see the loop start missing pulses as they come faster.
Watch a byte travel bit by bit on UART, I2C, SPI, and CAN, and see start bits, addresses, clock lines, acknowledgements, and CAN arbitration.
Add a computer, sensors, and motors to a robot and see its runtime, its peak current, and whether the battery can deliver it.
Spin a wheel past encoder ticks, read the A and B signals, and see how resolution and sample time limit speed estimates.
Tilt and spin a virtual IMU and see what its accelerometer and gyroscope report, including gravity and noise.
Integrate a gyroscope and an accelerometer with bias and noise, and watch heading error grow linearly and position error grow even faster.
Blend a noisy accelerometer and a drifting gyroscope with one slider, and see the fused tilt beat both.
Spin a robot in a circle near iron parts and fix its distorted compass readings with hard-iron and soft-iron calibration.
Move satellites across the sky and see how their geometry changes position error, then turn on RTK corrections.
Sweep an ultrasonic sensor around a room and see its wide beam, missed echoes from slanted walls, and false readings from multipath.
Sweep a 2D LiDAR around a room and see how angular resolution, range, glass, and dark surfaces shape the scan.
Spin a multi-beam LiDAR above a street scene and see its rings on the ground, and how few points land on a person far away.
Move a 3D object in front of a camera and see where it lands in the image as the focal length and distance change.
Bend a checkerboard grid with radial and tangential lens distortion, then recover the distortion from straight lines alone.
Move an object in depth in front of two cameras and see its disparity shrink, and the depth error grow, with distance.
Compare how a structured light camera and a time of flight camera see the same scene, and where each one fails: sunlight, glass, dark surfaces, and corners.
See how an FMCW radar turns a frequency chirp into range and speed, and how bandwidth decides whether two close objects can be told apart.
Watch a fast spinning bar through a normal camera and an event camera, and see blur in one and a clean stream of brightness changes in the other.
Press on a tactile skin to see contact location and force maps, and push on a tool tip to see the six numbers a wrist force-torque sensor reports.
Compare an absolute and an incremental encoder on a robot joint, then switch the power off while the arm sags and see which one still knows the angle.
Fuse a camera and a LiDAR on a turning robot and see how a camera delay that nobody accounts for makes the two disagree.
Find the pose of a camera relative to a LiDAR by lining up a target both sensors can see, first by hand and then by solving for it.
Load a DC motor and move along its torque-speed, current, power, and efficiency curves.
Change the gear ratio to trade speed for torque, then add backlash and watch the output lag when the input reverses.
Command a hobby servo with a pulse width and see its internal position loop, its speed limit, and what happens when the load is too heavy.
Step a stepper motor in full steps and microsteps, and see it miss steps when the speed or load is too high.
Rotate the stator field of a brushless motor with six-step commutation and with field-oriented control, and compare the torque ripple.
Drive a robot link into a wall with a stiff gearbox, a spring in series, and a low-ratio motor, and compare the impact force.
Change the four link lengths of a four-bar linkage and see whether it is a crank-rocker, a double crank, or a double rocker, with the curve its coupler traces.
Move the platform of a delta robot and watch its three arms solve their angles, inside the workspace the arms can reach.
Lift a load to a target height with an electric screw, a hydraulic cylinder, and a pneumatic cylinder, and compare force, stiffness, and overshoot.
Inflate the air chambers of a soft finger and watch it curl, then let it wrap around objects of different sizes.
Set the left and right wheel speeds and watch how a two-wheeled robot like the TurtleBot 4 drives, turns, and spins in place.
Drive a wheeled robot with forward speed and turn rate, try to slide it sideways, and watch it parallel park in several moves.
Steer a car-like robot and see why its two front wheels turn by different angles, where its turning center is, and its smallest turning circle.
Drive a mecanum base forward, sideways, diagonally, or spinning in place by mixing four wheel speeds.
Turn a tracked or skid-steer robot and see how its tracks must slide sideways to turn, and how much energy that wastes.
Step through wheel odometry one update at a time: read the wheel ticks, turn them into distance and turn, and add them to the pose.
Drive a robot around a square and compare where it really is with where its wheel encoders say it is. Small errors grow with every lap.
Turn the joints of a planar two-link arm to see forward kinematics, or click a target to have the arm solve inverse kinematics and reach it.
Build a three-joint arm one Denavit-Hartenberg row at a time and see where each row places the next frame.
Build forward kinematics from each joint's screw axis and the home pose, and check that it gives the same answer as the DH table.
Sweep the joint limits of a three-link arm and see its reachable workspace, and the smaller dexterous workspace where the tool can point any direction.
Spin each joint of a two-link arm and see the hand velocity it creates, and how the Jacobian adds them up.
Drive a two-link arm toward fully straight and fully folded, and watch its velocity ellipse flatten as it loses the ability to move one way.
Click a target and watch pseudoinverse and damped least squares inverse kinematics step a three-link arm toward it, or struggle near singularities.
Hold the hand of a three-link arm still and move its elbow anyway, using the motions that leave the hand unchanged.
Place the foot of a two-joint robot leg and see both knee solutions, then watch the leg follow a walking step.
Push a robot with its motors up a slope against friction, and see how mass, force, and incline set its acceleration and top speed.
Pull a block through a spring at steady speed and compare Coulomb, viscous, and stiction friction, including the jerky stick-slip that stiction causes.
Swing a pendulum and watch potential and kinetic energy trade back and forth, with and without damping, along with its phase portrait.
Try to balance a pole on a cart by pushing it left and right, then let an LQR controller do it and poke the pole to test it.
Move a two-link arm along a swinging path at different speeds and see which part of the joint torque dominates: inertia, Coriolis and centrifugal, or gravity.
Drop two balls with the same bounciness, one with an instant bounce rule and one with a spring-and-damper contact, and see bounce heights and sinking into the floor.
Rest a box on stiff ground in a simulator and raise the time step until it starts to jitter, bounce, and finally explode.
Accelerate a wheel on asphalt, wet road, and ice, see the slip curve that sets how much grip it has, and turn on traction control.
Reach out with a mobile manipulator's arm, add a payload, park it on a slope, and see when its center of mass leaves its wheelbase and it tips over.
Command thrust, roll, pitch, and yaw and see how the mixer turns them into four propeller speeds, and how the drone tilts and turns.
Trim an underwater robot's buoyancy, drive it into a current, and see how drag, added mass, and currents make underwater control hard.
Tune the P, I, and D gains and watch a robot drive to a target. See overshoot, oscillation, and steady-state error appear and disappear.
A robot moves along a line and gets noisy position readings. Watch the Kalman filter blend its motion model with each reading to track the robot.
Hundreds of guesses about where a robot might be, each scored against range readings to landmarks. Watch the cloud collapse onto the true pose.
Draw walls on a grid and watch A*, Dijkstra, and greedy search find a path. See how a good heuristic cuts down the search.
Longer guides you can read on screen or print. Every link inside is clickable.
A six-month self-study roadmap with curated resources, practice projects, and milestones. It assumes no prior electronics background and about two to three hours of work per day.
Adapted from work by Ronin (@deronin_) on X. The original ideas and structure are the original author's work.
Documentation, tools, courses, and help for the TurtleBot 4 on ROS 2 Jazzy and Ubuntu 24.04. Covers setup and networking, driving, sensors, simulation, mapping and navigation, and common fixes.
Original handout, written for this collection.
Ready to go further? The roadmap handout breaks robotics into six monthly steps, each with a goal and a signature build. Keep every build in its own GitHub repository, with a photo, your measured results, and a note on what broke and how you fixed it.
Read a schematic, build a working circuit, and find faults.
Build a robot that moves, senses, and corrects itself.
Design a part, make it, and have it fit.
Simulate a robot that maps and navigates on its own.
Understand the math under the libraries.
Pick a direction, finish a portfolio piece, and apply.