Robotic Arm Inverse Kinematics
Advanced
Control 2D robotic arm to reach target position. State: [joint angles]. Actions: [joint torques]. Reward: -dist(endpoint, target) - action_cost.
The problem, from first principles
Arm endpoint position is nonlinear function of joint angles. RL must learn inverse kinematics: given target, find joint angles.
From theory to code
Implement compute_arm_kinematics(joint_angles, link_lengths) which:
- Takes joint angles and link lengths
- Computes endpoint position using forward kinematics
- Returns (x, y) position of end-effector
Constraints
- 2D arm with two joints (DOF=2)
- Link lengths fixed: [L1, L2]
- Actions affect joint angles
- Dense reward based on distance to target
Hints
Hint 1: Forward kinematics
x = L1*cos(θ1) + L2*cos(θ1+θ2), similar for yHint 2: Inverse problem
Goal: find θ1, θ2 given target (x,y)Hint 3: Action scaling
Torques should be integrated to update joint anglesKeywords
rlroboticscontinuous-controlinverse-kinematics
Python
Run your code to see results
No results yet
Run your code to check it against the examples, or submit to run every test.