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Inverse Kinematics & Arm Reach

Comprehensive notes, formulas, and practice questions for Inverse Kinematics & Arm Reach.

Inverse Kinematics & Arm Reach

Inverse Kinematics for Robotic Arms

Core Idea

Forward kinematics asks: given joint angles, where is the end-effector? Inverse kinematics (IK) flips the question: given a desired end-effector position (x,y)(x, y), what joint angles θ1\theta_1 and θ2\theta_2 produce it? IK is what lets a robot arm reach out and grab an object at a known location.

Key Formula / Algorithm

For a 2-link planar arm with link lengths l1l_1 and l2l_2:

Step 1 — find θ2\theta_2 using the law of cosines:

cosθ2=x2+y2l12l222l1l2\cos\theta_2 = \frac{x^2 + y^2 - l_1^2 - l_2^2}{2\,l_1\,l_2}

θ2=±arccos ⁣(x2+y2l12l222l1l2)\theta_2 = \pm\arccos\!\left(\frac{x^2 + y^2 - l_1^2 - l_2^2}{2\,l_1\,l_2}\right)

The ±\pm gives two solutions: elbow-up and elbow-down.

Step 2 — find θ1\theta_1:

θ1=atan2(y,x)atan2 ⁣(l2sinθ2,  l1+l2cosθ2)\theta_1 = \operatorname{atan2}(y,\,x) - \operatorname{atan2}\!\left(l_2\sin\theta_2,\; l_1 + l_2\cos\theta_2\right)

How It Works (Step by Step)

  1. Measure the straight-line distance from base to target: r=x2+y2r = \sqrt{x^2 + y^2}.
  2. Check reachability: the target must satisfy l1l2rl1+l2|l_1 - l_2| \le r \le l_1 + l_2.
  3. Apply the cosine rule to find θ2\theta_2 (two solutions).
  4. Substitute each θ2\theta_2 into the atan2 formula to get the matching θ1\theta_1.
  5. Choose the solution (elbow-up or elbow-down) based on workspace constraints.

Real-World Application

Every industrial robot welding a car frame, every surgical robot making a precise incision, and every animated video-game character reaching for an object uses IK. In robot arms like the KUKA or UR5, IK runs hundreds of times per second so the end-effector tracks a moving target smoothly.

Quick Check

  1. A 2-link arm has l1=l2=1ml_1 = l_2 = 1\,\text{m}. What is θ2\theta_2 when the target is at (1,0)(1, 0)? (Hint: substitute into the cosine formula.)
  2. Why does IK sometimes have two solutions, and why might a robot prefer one over the other?

Key Takeaways (TL;DR)

  • Core Idea
  • Key Formula / Algorithm
  • How It Works (Step by Step)
  • Real-World Application

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