Learn AIGeometry and control foundations
Describe positions and orientations with named frames, then build toward verified simulated motion.
What you’ll explore
- Coordinate frames
- Forward kinematics
- Units
- Reachability
- 3D rotations
- Quaternions
Your lessons
0 / 12 completeDescribe where the robot is
Move a two-link arm, express points in named frames and distinguish ideal reach from verified motion.
Represent motion in three dimensions
Compare fixed and moving axes, matrix and quaternion descriptions, and the limits of a projected 3D picture.
Use a Jacobian
Predict small tool movements, inspect missing directions and compare inverse velocity proposals.
Turn a target into motion
Find alternative target-reaching postures and separate geometric reach, joint limits and obstacle contact.
Correct errors using feedback
Tune an ideal cart controller and inspect overshoot, velocity damping and delayed measurements.
Choose continuous actions
Train a small force controller, then compare continuous outputs, discrete choices, noise and saturation.
Stop when the controller leaves its limits
Inspect runtime rejection, delayed observations and bounded fallback without equating a stopped task with success.
Turn observations into estimates
Distinguish noisy sensor readings, delayed information, filtered estimates and simulator truth.
Fuse noisy measurements
Predict motion, correct with sensors and inspect the uncertainty assumptions of a linear Kalman filter.
Reason about forces and contact
Compare force and position commands, friction limits and the forces needed to hold a load.
Plan a collision-free trajectory
Search joint-space waypoints, try shortcuts and independently verify the full motion.
Enforce operating limits
Keep learned proposals separate from action checks, watchdogs, collision prevention and latched braking.