Make the foundations concrete.

Build working knowledge of robotics and machine learning through examples you can change, calculations you can check, and data you can inspect.

Start with the map of machine learning fields to connect tasks, data, learning signals, and model choices.

41 lessons found

Foundations first
  1. Foundations / 12 min read

    Joint limits in inverse kinematics: solve a bounded velocity step

    Turn physical joint ranges and speed limits into bounds on a local inverse-kinematics command. Compare a constrained least-squares solution with clipping, and check the resulting finite arm position.

  2. Foundations / 13 min read

    Analytical inverse kinematics: find both arm configurations for a target

    Derive both joint-angle solutions for a two-link robot arm, check them with forward kinematics, and identify unreachable targets and merged boundary branches.

  3. Foundations / 11 min read

    Robot workspaces: derive the reachable position set

    Derive the exact position workspace of a two-link robot with elbow limits. Test targets against its annulus, recover a valid arm configuration, and separate position reach from orientation and path feasibility.

  4. Foundations / 13 min read

    Configuration space: follow joint paths across angle boundaries

    Represent a robot arm as a point in joint space, follow paths across periodic angle boundaries, and distinguish angular distance from workspace motion and collision clearance.

  5. Foundations / 11 min read

    Collision checking: test the motion between endpoints

    Check a translating disk against a circular obstacle, including every point between its endpoints. Derive the closest-point test, expose missed samples, and distinguish broad-phase box overlap from a collision.