Developed a Python application to simulate robotic arm forward kinematics and inverse kinematics for arbitrary arm configurations.
Linear algebra calculations for end-effector position are handled using NumPy, with real-time visualisation powered by PyGame. Reduced testing time by 91% by simplifying linear transformations.
Utilised NumPy to handle matrix multiplication for forward and inverse kinematics of a robotic arm, calculating end-effector position for arbitrary joint configurations.
Leveraged PyGame to fully visualise robot end-effector and joint positions, allowing the user to input different angles while simultaneously showing output positions in real time.
Forward and inverse kinematics ended up having multiple valid solutions, so it was difficult to pick the shortest path. A lot of math went into picking the optimal and realistic distance.
Keeping the PyGame rendering in sync with the simulation state at variable frame rates without the visual lagging behind the computed positions.