In this section, we’ll build intuition for kinematics. Which is the math that links joint angles to end‑effector positions i.e. where is the hand given the joints? We will do this by walking through a concrete example.
Let’s explore how traditional robotics approaches robot control through a concrete example.
We start with a familiar robot and simplify it so we can reason step by step without losing the key ideas.
The SO-100 arm simplified to a 2D planar manipulator by constraining some joints.
The SO-100 is a 6-degree-of-freedom (6-DOF) robot arm. To understand the principles, let’s simplify it to a 2-DOF planar manipulator by constraining some joints.
To keep the math clear, our simplified robot has:
Question: Given joint angles θ₁ and θ₂, where is the end-effector?
Answer: We can calculate the end-effector position mathematically:
This is called Forward Kinematics (FK) - mapping from joint space to task space.
Understanding the Math: This equation comes from basic trigonometry!
Why it matters: FK is relatively easy - given joint angles, we can always compute where the robot’s hand is. The hard part is the reverse…
Now let’s try to invert the mapping: given a desired hand position, what joints achieve it?
Question: Given a desired end-effector position p*, what joint angles should we use?
Answer: This is Inverse Kinematics (IK) - much harder to solve!
We need to solve: $p(q) = p^*$
In general, this becomes an optimization problem:
Why IK is Hard:
This is why robotics engineers spend so much time on IK algorithms!
Free to move
Constrained by floor
Multiple obstacles
Real robots face constraints:
These constraints make the feasible configuration space $\mathcal{Q}$ much more complex!
Even for this simple 2-DOF robot, solving IK with constraints is non-trivial. Real robots have:
Traditional approaches require extensive mathematical modeling and expert knowledge for each specific case.
Mental model: FK is a direct calculator (q → p) and is usually easy; IK is a search (p → q) and becomes hard as soon as you add workspace limits, obstacles, or joint constraints. When IK gets brittle, we’ll switch to differential reasoning (velocities) in the next step.