Velocity of 6-Joint Robot Arm – Translation
lesson
For a real 6-link robot our previous approach to computing the Jacobian becomes unwieldy so we will instead compute a numerical approximation to the forward kinematic function.
lesson
For a real 6-link robot our previous approach to computing the Jacobian becomes unwieldy so we will instead compute a numerical approximation to the forward kinematic function.
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We summarise the important points from this masterclass.
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The end-effector is not able to move equally fast in all directions, and that in fact depends on the pose of the robot. We will introduce the velocity ellipse to illustrate this.
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For a simple 2-link planar robot we introduce and derive its Jacobian matrix, and also introduce the concept of spatial velocity.
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We consider a robot, which has two rotary joints and an arm.
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We learn how to describe the orientation of an object by a 3×3 rotation matrix which has some special properties.
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We will learn about how we make the the robot joints move to the angles or positions that are required in order to achieve the desired end-effector motion. This is the job of the robot’s joint controller and in this lecture we will learn how this works. This journey will take us in to the […]
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We revisit the simple 2-link planar robot and determine the inverse kinematic function using simple geometry and trigonometry.
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As we did for the simple planar robots we can invert the Jacobian and perform resolved-rate motion control.
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Let’s look at numerical approaches to inverse kinematics for a couple of different robots and learn some of the important considerations. For RTB10.x please note that the mask value must be explicitly preceded by the ‘mask’ keyword. For example: >> q = p2.ikine(T, [-1 -1], ‘mask’, [1 1 0 0 0 0])