Distance Between Two Lines in 3d

Here you will learn formula to find the distance between two lines in 3d in both vector form and cartesian form with example.

Letโ€™s begin โ€“

Distance Between Two Lines in 3d

(a) Vector Form

Let \(l_1\) and \(l_2\) be two lines having vector equations

\(l_1\) : \(\vec{r}\) =ย \(\vec{a_1}\) + \(\lambda\)\(\vec{b_1}\)

and \(l_2\) : \(\vec{r}\) = \(\vec{a_2}\) + \(\mu\)\(\vec{b_2}\)

The shortest distance (S.D.) between two the two non-parallel lines \(\vec{r}\) = \(\vec{a_1}\) + \(\lambda\)\(\vec{b_1}\) and \(\vec{r}\) = \(\vec{a_2}\) + \(\mu\)\(\vec{b_2}\) is given by

S.D. = |\((\vec{b_1} \times \vec{b_2}).(\vec{a_2} -\vec{ a_1})\over |\vec{b_1} \times \vec{b_2}|\)|

Condition for two given lines to intersect :ย If given lines intersect, then the shortest distance between them is zero.

\((\vec{b_1} \times \vec{b_2}).(\vec{a_2} -\vec{ a_1})\) = 0

(b) Cartesian Form

Let the cartesian equation of two skew lines be

\(x โ€“ x_1\over l_1\) = \(y โ€“ y_1\over m_1\) = \(z โ€“ z_1\over n_1\)

and \(x โ€“ x_2\over l_2\) = \(y โ€“ y_2\over m_2\) = \(z โ€“ z_2\over n_2\)

Shortest Distance (S.D.) = \(\begin{vmatrix} x_2 โ€“ x_1 & y_2 โ€“ y_1 &ย  z_2 โ€“ z_1 \\ย  l_1 & m_1 & n_1 \\ย  l_2 & m_2 & n_2 \end{vmatrix}\over \sqrt{(m_1n_2 โ€“ m_2n_1)^2 + (n_1l_1 โ€“ l_1n_2)^2 + (l_1m_2 โ€“ l_2m_1)^2}\)

Condition for two given lines to intersect :ย If given lines intersect, then the shortest distance between them is zero.

\(\begin{vmatrix} x_2 โ€“ x_1 & y_2 โ€“ y_1 &ย  z_2 โ€“ z_1 \\ย  l_1 & m_1 & n_1 \\ย  l_2 & m_2 & n_2 \end{vmatrix}\) = 0

Example : Find the shortest distance between the lines

\(\vec{r}\) = (\(4\hat{i} โ€“ \hat{j}\)) + \(\lambda\)(\(\hat{i} + 2\hat{j} โ€“ 3\hat{k}\))

and \(\vec{r}\) = (\(\hat{i} โ€“ \hat{j} + 2\hat{k}\)) + \(\mu\)(\(2\hat{i} + 4\hat{j} โ€“ 5\hat{k}\))

Solution : We know that the shortest distance between two lines \(\vec{r}\) = \(\vec{a_1}\) + \(\lambda\)\(\vec{b_1}\) and \(\vec{r}\) = \(\vec{a_2}\) + \(\mu\)\(\vec{b_2}\) is given by

d = |\((\vec{b_1} \times \vec{b_2}).(\vec{a_2} -\vec{ a_1})\over |\vec{b_1} \times \vec{b_2}|\)|

Comparing the given equation with the equations \(\vec{r}\) = \(\vec{a_1}\) + \(\lambda\)\(\vec{b_1}\) and \(\vec{r}\) = \(\vec{a_2}\) + \(\mu\)\(\vec{b_2}\) respectively.

\(\vec{a_1}\) = \(4\hat{i} โ€“ \hat{j}\), \(\vec{a_2}\) = \(\hat{i} โ€“ \hat{j} + 2\hat{k}\)

and \(\vec{b_1}\) = \(\hat{i} + 2\hat{j} โ€“ 3\hat{k}\), \(\vec{b_2}\) = \(2\hat{i} + 4\hat{j} โ€“ 5\hat{k}\)

\(a_2 โ€“ a_1\) = \(-3\hat{i} + 0\hat{j} + 2\hat{k}\)

and \(b_1\times b_2\) = \(\begin{vmatrix} \hat{i} & \hat{j} &ย  \hat{k} \\ย  1 & 2 & -3 \\ย  2 & 4 & -5 \end{vmatrix}\) = \(2\hat{i} โ€“ \hat{j} + 0\hat{k}\)

(\(a_2 โ€“ a_1\)).(\(b_1\times b_2\)) = \(-3\hat{i} + 0\hat{j} + 2\hat{k}\).\(2\hat{i} โ€“ \hat{j} + 0\hat{k}\) = -6 + 0 + 0 = 0

and | \(b_1\times b_2\) | = \(\sqrt{4 + 1 + 0}\) = \(\sqrt{5}\)

\(\therefore\) Shortest Distance = |\((\vec{b_1} \times \vec{b_2}).(\vec{a_2} -\vec{ a_1})\over |\vec{b_1} \times \vec{b_2}|\)|ย 

= |\(-6\over \sqrt{5}\)| = \(6\over \sqrt{5}\)

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