Robot Arm Simulator

In this project a 2 DoF robot arm is simulated in a 2D space. The environment has some obstacles in it, which might interfere with robot's movement. The project includes three part:

1. Inverse Kinematics
2. Obstacle Avoidance and Path Planning
3. Motion Actuator

Inverse Kinematics

The inverse kinematics task is to build in order to transform position from cartesian coordination into robots joint angle coordination. The corresponding code in JavaScripts is demonstrated below:

// x and y is the input value in cartesian coordination
let dx = x*x + y*y;
let dl = arm_1.len*arm_1.len + arm_2.len*arm_2.len;

if (dx > dl)
    return;

var q2 = Math.acos((dx - dl) / (2*arm_1.len*arm_2.len));
var k1 = arm_1.len + arm_2.len * Math.cos(q2);
var k2 = arm_2.len * Math.sin(q2);
var q1 = Math.atan2(y, -x) - Math.atan2(k2, k1);

theta_1 = -(q1 - Math.PI);
theta_2 = -(q2 - Math.PI);

Path Planning

In order to avoid obstacles in this code, a RRT path planning is employed. In this method, robot tries to avoid obstacles in joint space. Hence, we can make sure it will never hit any obstacles in its way.

Motion Actuator

In order to transform robot position from joint space to cartesian space we just simply calculate each joint position node-by-node. The code example is demonstrated below:

// Normalizing angles
theta_1 = 6.0 * cursor.x / 400.0 + .07;
theta_2 = 6.0 * cursor.y / 400.0 + .07;

// Calculating joint #1
let eef_x = Math.cos(interest_point.t1) * arm_1.len + arm_1.x;
let eef_y = Math.sin(interest_point.t1) * arm_1.len + arm_1.y;

// Calculating joint #2
let eef_x2 = Math.cos(interest_point.t1 + interest_point.t2 + Math.PI) * arm_2.len + eef_x;
let eef_y2 = Math.sin(interest_point.t1 + interest_point.t2 + Math.PI) * arm_2.len + eef_y;

end_effector_x = eef_x2;
end_effector_y = eef_y2;